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<div id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style="color: rgb(18, 18, 18);"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(18, 18, 18);"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(18, 18, 18);"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(18, 18, 18);"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(18, 18, 18);"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(18, 18, 18);"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(18, 18, 18);"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(18, 18, 18);"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(18, 18, 18);"><div style="color: rgb(18, 18, 18); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(18, 18, 18);"><h4 style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Summary of course content</h4><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">An appreciation and understanding of individual, social and cultural diversity, continuity, and change in social life is always needed. This course aims to help students stimulate their understanding of cultural and political issues and contemporary social situations. To pursue a career in social work, politics, law, and marketing, this A-level course will be the first and most crucial step to make for your dream career.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">By studying this Cambridge International AS &amp; A Level course, candidates will develop:</p><ul fr-original-style="" style="box-sizing: border-box;"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">knowledge and understanding of sociological terms, theories, methods and research findings</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">&nbsp;an awareness of the range and limitations of sociological theory and the ability to compare and contrast different theoretical perspectives</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">an appreciation and understanding of individual, social and cultural diversity and of continuity and change in social life</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">an understanding of sociological research methods, including issues concerned with the planning, implementation and evaluation of research enquiry and the collection, analysis and interpretation of data</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">improved skills in communication, interpretation, analysis and evaluation</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">skills for further study</li></ul></div><div style="color: rgb(18, 18, 18); box-sizing: border-box;" fr-original-style=" color: rgb(18, 18, 18);"><h4 style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Candidates study the following content:</h4><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">1. Socialisation, identity and methods of research</p><ul fr-original-style="" style="box-sizing: border-box;"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Socialisation and the creation of social identity</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">The process of learning and socialisation</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Social control, conformity and resistance</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Social identity and change</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Methods of research</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Types of data, methods and research design</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Approaches to Sociological Research</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Research issues</li></ul><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">2. The Family</p><ul fr-original-style="" style="box-sizing: border-box;"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Theories of family and social change</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Perspectives on the role of the family</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Diversity and social change</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Family roles and changing relationships</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Gender equality and experiences of family life</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Age and family life</li></ul><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">3. Education</p><ul fr-original-style="" style="box-sizing: border-box;"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Education and society</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Theories about the role of education</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Education and Social Mobility</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Influences on the curriculum</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Education and inequality</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Intelligence and educational attainment</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Social class and educational attainment</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Ethnicity and educational attainment</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Gender and educational attainment</li></ul><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">4. Globalisation, Media and Religion</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">A. Globalisation</p><ul fr-original-style="" style="box-sizing: border-box;"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Key debates, concepts and perspectives</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Perspectives on globalisation</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Globalisation and identity</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Globalisation, power and politics</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Contemporary issues</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Globalisation, poverty and inequalities</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Globalisation and migration</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Globalisation and crime</li></ul><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">B. Media</p><ul fr-original-style="" style="box-sizing: border-box;"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Ownership and control of the media</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Traditional media and the new media</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Theories of the media and influences on media content</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">The impact of the new media</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Media representation and effects</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Media representations of class, gender, ethnicity, and age groups</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Different models of media effects</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">The impact of the media on behaviour</li></ul><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">C. Religion</p><ul fr-original-style="" style="box-sizing: border-box;"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Religion and social order</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Religion and Society</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Religion and social order</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Religion as a source of social change</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">The influence of religion</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">The secularisation debate</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Gender, feminism and religion</li><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Religion and post-modernity</li></ul></div></div></div></div></div></div></div></div></div></div></div></div><div style="color: rgb(18, 18, 18); box-sizing: border-box;" fr-original-style=" color: rgb(18, 18, 18);"><br fr-original-style="" style="box-sizing: border-box;"></div>

Summary of course content
An appreciation and understanding of individual, social and cultural diversity, continuity, and change in social life is always needed. This course aims to help students stimulate their understanding of cultural and political issues and contemporary social situations. To pursue a career in social work, politics, law, and marketing, this A-level course will be the first and most crucial step to make for your dream career.
By studying this Cambridge International AS & A Level course, candidates will develop:
knowledge and understanding of sociological terms, theories, methods and research findings
an awareness of the range and limitations of sociological theory and the ability to compare and contrast different theoretical perspectives
an appreciation and understanding of individual, social and cultural diversity and of continuity and change in social life
an understanding of sociological research methods, including issues concerned with the planning, implementation and evaluation of research enquiry and the collection, analysis and interpretation of data
improved skills in communication, interpretation, analysis and evaluation
skills for further study
Candidates study the following content:
1. Socialisation, identity and methods of research
Socialisation and the creation of social identity
The process of learning and socialisation
Social control, conformity and resistance
Social identity and change
Methods of research
Types of data, methods and research design
Approaches to Sociological Research
Research issues
2. The Family
Theories of family and social change
Perspectives on the role of the family
Diversity and social change
Family roles and changing relationships
Gender equality and experiences of family life
Age and family life
3. Education
Education and society
Theories about the role of education
Education and Social Mobility
Influences on the curriculum
Education and inequality
Intelligence and educational attainment
Social class and educational attainment
Ethnicity and educational attainment
Gender and educational attainment
4. Globalisation, Media and Religion
A. Globalisation
Key debates, concepts and perspectives
Perspectives on globalisation
Globalisation and identity
Globalisation, power and politics
Contemporary issues
Globalisation, poverty and inequalities
Globalisation and migration
Globalisation and crime
B. Media
Ownership and control of the media
Traditional media and the new media
Theories of the media and influences on media content
The impact of the new media
Media representation and effects
Media representations of class, gender, ethnicity, and age groups
Different models of media effects
The impact of the media on behaviour
C. Religion
Religion and social order
Religion and Society
Religion and social order
Religion as a source of social change
The influence of religion
The secularisation debate
Gender, feminism and religion
Religion and post-modernity

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Sociology

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AS Sociology

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<strong>Implement machine learning-based clustering and classification in Python for pattern recognition and data analysis</strong>
        <p>In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By becoming proficient in unsupervised and supervised learning in Python, you can give your company a competitive edge and level up in your career. This course will give you a robust grounding in clustering and classification, the main aspects of machine learning.

The course consists of 7 sections that will help you master Python machine learning. You'll begin with an introduction to Python data science and Anaconda, which is a powerful Python-driven framework for data science. Next, you'll delve into Pandas and read data structures, including CSV, Excel, and HTML data. As you advance, you'll perform data cleaning and munging to remove NAs\no data and discover how to handle conditional data, group by attributes, and do much more. You'll also grasp basic concepts of unsupervised learning such as K-means clustering and its implementation on the Iris dataset. The course will take you through the theory of dimension reduction and feature selection for machine learning and help you understand Principal Component Analysis (PCA) using two case studies. You'll get to grips with the linear and non-linear classification of SVM along with Gradient Boosting Machine (GBM) and Naive Bayes Classification. Finally, you'll explore neural networks and discover the powerful H20 framework and for deep learning classification. Additionally, you'll learn about perceptrons and Artificial Neural Networks (ANN) for binary classification.
By the end of this course, you'll be able to use packages such as NumPy, Pandas, and Matplotlib to work with real data in Python.

All code and supporting files for this course are available at 
https://github.com/sanjanapackt/PacktPublishing-Clustering-and-Classification-with-Machine-Learning-in-Python.</p>
        <h2>What You Will Learn</h2><p>Harness the power of Anaconda/iPython for practical data science<br>Read data into the Python environment from different sources<br>Carry out basic data preprocessing and wrangling in Python<br>Implement unsupervised/clustering techniques such as k-means clustering<br>Get to grips with dimensionality reduction techniques and feature selection<br>Implement supervised learning/classification techniques such as random forests<br>Explore neural network- and deep learning-based classification<br></p>
        <h2>Audience</h2><p>If you want to build data science applications in the Python environment, this book is for you. You'll also find this book helpful if you want to learn how to implement unsupervised learning on real data using Python, or if you're a student looking to get started with artificial neural networks and deep learning.</p>
        <h2>Approach</h2><p>This course is full of interesting and illustrative examples and easy-to-understand theory to help you implement a real-world concept in every lecture. It covers hands-on methods to simplify and address even the most difficult concepts in Python using minimal jargon.</p>
        <h2>Key Features</h2><p>Explore the most important Python data science concepts and packages, including Pandas * Master the Anaconda framework and use it to implement clustering and classification models on your data * Get to grips with data science fundamentals and understand which models should be used when * </p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/clustering-and-classification-with-machine-learning-in-r</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Welcome to Clustering & Classification with Machine Learning in Python</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: Welcome to Clustering & Classification with Machine Learning in Python</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Machine Learning?</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: What is Machine Learning?</p></td></tr><tr><td style='padding: 15px;'><p>3. Python Data Science Environment</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: Python Data Science Environment</p></td></tr><tr><td style='padding: 15px;'><p>4. For Mac Users</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: For Mac Users</p></td></tr><tr><td style='padding: 15px;'><p>5. IPython in Browser</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: IPython in Browser</p></td></tr><tr><td style='padding: 15px;'><p>6. Python Data Science Packages to Be Used</p><p style='margin: 0'>INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: Python Data Science Packages to Be Used</p></td></tr></tbody></table><br><h4>2. Read in Data from Different Sources with Pandas</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What are Pandas?</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: What are Pandas?</p></td></tr><tr><td style='padding: 15px;'><p>2. Read in Data from CSV</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in Data from CSV</p></td></tr><tr><td style='padding: 15px;'><p>3. Read in Online CSV</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in Online CSV</p></td></tr><tr><td style='padding: 15px;'><p>4. Read in Excel Data</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in Excel Data</p></td></tr><tr><td style='padding: 15px;'><p>5. Read in HTML Data</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in HTML Data</p></td></tr><tr><td style='padding: 15px;'><p>6. Read in Data from Databases</p><p style='margin: 0'>Read in Data from Different Sources with Pandas: Read in Data from Databases</p></td></tr></tbody></table><br><h4>3. Data Cleaning & Munging</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Remove Missing Values</p><p style='margin: 0'>Data Cleaning & Munging: Remove Missing Values</p></td></tr><tr><td style='padding: 15px;'><p>2. Conditional Data Selection</p><p style='margin: 0'>Data Cleaning & Munging: Conditional Data Selection</p></td></tr><tr><td style='padding: 15px;'><p>3. Data Grouping</p><p style='margin: 0'>Data Cleaning & Munging: Data Grouping</p></td></tr><tr><td style='padding: 15px;'><p>4. Data Sub setting</p><p style='margin: 0'>Data Cleaning & Munging: Data sub setting</p></td></tr><tr><td style='padding: 15px;'><p>5. Ranking & Sorting</p><p style='margin: 0'>Data Cleaning & Munging: Ranking & Sorting</p></td></tr><tr><td style='padding: 15px;'><p>6. Concatenate</p><p style='margin: 0'>Data Cleaning & Munging: Concatenate</p></td></tr><tr><td style='padding: 15px;'><p>7. Merging & Joining Data Frames</p><p style='margin: 0'>Data Cleaning & Munging: Merging & Joining Data Frames</p></td></tr></tbody></table><br><h4>4. Unsupervised Learning in Python</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Unsupervised Classification- Some Basic Concepts</p><p style='margin: 0'>Unsupervised Learning in Python: Unsupervised Classification- Some Basic Concepts</p></td></tr><tr><td style='padding: 15px;'><p>2. K-Means Clustering: Theory</p><p style='margin: 0'>Unsupervised Learning in Python: K-Means Clustering: Theory</p></td></tr><tr><td style='padding: 15px;'><p>3. Implement K-Means on the Iris Data</p><p style='margin: 0'>Unsupervised Learning in Python: Implement K-Means on the Iris Data</p></td></tr><tr><td style='padding: 15px;'><p>4. Quantifying K-Means Clustering Performance</p><p style='margin: 0'>Unsupervised Learning in Python: Quantifying K-Means Clustering Performance</p></td></tr><tr><td style='padding: 15px;'><p>5. K-Means Clustering with Real Data</p><p style='margin: 0'>Unsupervised Learning in Python: K-Means Clustering with Real Data</p></td></tr><tr><td style='padding: 15px;'><p>6. How to Select the Optimal Number of Clusters?</p><p style='margin: 0'>Unsupervised Learning in Python: How to Select the Optimal Number of Clusters?</p></td></tr><tr><td style='padding: 15px;'><p>7. Gaussian Mixture Modelling (GMM)</p><p style='margin: 0'>Unsupervised Learning in Python: Gaussian Mixture Modelling (GMM)</p></td></tr><tr><td style='padding: 15px;'><p>8. Hierarchical Clustering-theory</p><p style='margin: 0'>Unsupervised Learning in Python: Hierarchical Clustering-theory</p></td></tr><tr><td style='padding: 15px;'><p>9. Hierarchical Clustering-practical</p><p style='margin: 0'>Unsupervised Learning in Python: Hierarchical Clustering-practical</p></td></tr></tbody></table><br><h4>5. Dimension Reduction & Feature Selection for Machine Learning</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Principal Component Analysis (PCA)-Theory</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Principal Component Analysis (PCA)-Theory</p></td></tr><tr><td style='padding: 15px;'><p>2. Principal Component Analysis (PCA)-Case Study 1</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Principal Component Analysis (PCA)-Case Study 1</p></td></tr><tr><td style='padding: 15px;'><p>3. Principal Component Analysis (PCA)-Case Study 2</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Principal Component Analysis (PCA)-Case Study 2</p></td></tr><tr><td style='padding: 15px;'><p>4. Linear Discriminant Analysis (LDA) for Dimension Reduction</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Linear Discriminant Analysis (LDA) for Dimension Reduction</p></td></tr><tr><td style='padding: 15px;'><p>5. t-SNE Dimension Reduction</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: t-SNE Dimension Reduction</p></td></tr><tr><td style='padding: 15px;'><p>6. Feature Selection to Select the Most Relevant Predictors</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Feature Selection to Select the Most Relevant Predictors</p></td></tr><tr><td style='padding: 15px;'><p>7. Recursive Feature Elimination (RFE)</p><p style='margin: 0'>Dimension Reduction & Feature Selection for Machine Learning: Recursive Feature Elimination (RFE)</p></td></tr></tbody></table><br><h4>6. Supervised Learning: Classification</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Concepts Behind Supervised Learning</p><p style='margin: 0'>Supervised Learning: Classification: Concepts Behind Supervised Learning</p></td></tr><tr><td style='padding: 15px;'><p>2. Data Preparation for Supervised Learning</p><p style='margin: 0'>Supervised Learning: Classification: Data Preparation for Supervised Learning</p></td></tr><tr><td style='padding: 15px;'><p>3. Pointers on Evaluating the Accuracy of Classification Modelling</p><p style='margin: 0'>Supervised Learning: Classification: Pointers on Evaluating the Accuracy of Classification Modelling</p></td></tr><tr><td style='padding: 15px;'><p>4. Using Logistic Regression as a Classification Model</p><p style='margin: 0'>Supervised Learning: Classification: Using Logistic Regression as a Classification Model</p></td></tr><tr><td style='padding: 15px;'><p>5. kNN- Classification</p><p style='margin: 0'>Supervised Learning: Classification: kNN- Classification</p></td></tr><tr><td style='padding: 15px;'><p>6. Naive Bayes Classification</p><p style='margin: 0'>Supervised Learning: Classification: Naive Bayes Classification</p></td></tr><tr><td style='padding: 15px;'><p>7. Linear Discriminant Analysis</p><p style='margin: 0'>Supervised Learning: Classification: Linear Discriminant Analysis</p></td></tr><tr><td style='padding: 15px;'><p>8. SVM- Linear Classification</p><p style='margin: 0'>Supervised Learning: Classification: SVM- Linear Classification</p></td></tr><tr><td style='padding: 15px;'><p>9. Non-Linear SVM Classification</p><p style='margin: 0'>Supervised Learning: Classification: Non-Linear SVM Classification</p></td></tr><tr><td style='padding: 15px;'><p>10. RF-Classification</p><p style='margin: 0'>Supervised Learning: Classification: RF-Classification</p></td></tr><tr><td style='padding: 15px;'><p>11. Gradient Boosting Machine (GBM)</p><p style='margin: 0'>Supervised Learning: Classification: Gradient Boosting Machine (GBM)</p></td></tr><tr><td style='padding: 15px;'><p>12. Voting Classifier</p><p style='margin: 0'>Supervised Learning: Classification: Voting Classifier</p></td></tr></tbody></table><br><h4>7. Neural Networks and Deep Learning Based Classification Techniques</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Perceptrons for Binary Classification</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Perceptrons for Binary Classification</p></td></tr><tr><td style='padding: 15px;'><p>2. Artificial Neural Networks (ANN) for Binary Classification</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Artificial Neural Networks (ANN) for Binary Classification</p></td></tr><tr><td style='padding: 15px;'><p>3. Multi-class Classification With MLP</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Multi-class Classification With MLP</p></td></tr><tr><td style='padding: 15px;'><p>4. Introduction to H20</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Introduction to H20</p></td></tr><tr><td style='padding: 15px;'><p>5. Use H20 for Deep Learning Classification</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: Use H20 for Deep Learning Classification</p></td></tr><tr><td style='padding: 15px;'><p>6. H20 Deep Learning for Classification</p><p style='margin: 0'>Neural Networks and Deep Learning Based Classification Techniques: H20 Deep Learning for Classification</p></td></tr></tbody></table>

Implement machine learning-based clustering and classification in Python for pattern recognition and data analysis
In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By becoming proficient in unsupervised and supervised learning in Python, you can give your company a competitive edge and level up in your career. This course will give you a robust grounding in clustering and classification, the main aspects of machine learning. The course consists of 7 sections that will help you master Python machine learning. You'll begin with an introduction to Python data science and Anaconda, which is a powerful Python-driven framework for data science. Next, you'll delve into Pandas and read data structures, including CSV, Excel, and HTML data. As you advance, you'll perform data cleaning and munging to remove NAs\no data and discover how to handle conditional data, group by attributes, and do much more. You'll also grasp basic concepts of unsupervised learning such as K-means clustering and its implementation on the Iris dataset. The course will take you through the theory of dimension reduction and feature selection for machine learning and help you understand Principal Component Analysis (PCA) using two case studies. You'll get to grips with the linear and non-linear classification of SVM along with Gradient Boosting Machine (GBM) and Naive Bayes Classification. Finally, you'll explore neural networks and discover the powerful H20 framework and for deep learning classification. Additionally, you'll learn about perceptrons and Artificial Neural Networks (ANN) for binary classification.
By the end of this course, you'll be able to use packages such as NumPy, Pandas, and Matplotlib to work with real data in Python. All code and supporting files for this course are available at https://github.com/sanjanapackt/PacktPublishing-Clustering-and-Classification-with-Machine-Learning-in-Python.
What You Will Learn
Harness the power of Anaconda/iPython for practical data science
Read data into the Python environment from different sources
Carry out basic data preprocessing and wrangling in Python
Implement unsupervised/clustering techniques such as k-means clustering
Get to grips with dimensionality reduction techniques and feature selection
Implement supervised learning/classification techniques such as random forests
Explore neural network- and deep learning-based classification

Audience
If you want to build data science applications in the Python environment, this book is for you. You'll also find this book helpful if you want to learn how to implement unsupervised learning on real data using Python, or if you're a student looking to get started with artificial neural networks and deep learning.
Approach
This course is full of interesting and illustrative examples and easy-to-understand theory to help you implement a real-world concept in every lecture. It covers hands-on methods to simplify and address even the most difficult concepts in Python using minimal jargon.
Key Features
Explore the most important Python data science concepts and packages, including Pandas * Master the Anaconda framework and use it to implement clustering and classification models on your data * Get to grips with data science fundamentals and understand which models should be used when * 
Github Repo
https://github.com/packtpublishing/clustering-and-classification-with-machine-learning-in-r
About the Author
Minerva Singh
Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.
Course Outline
1. INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools

1. Welcome to Clustering & Classification with Machine Learning in Python
INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: Welcome to Clustering & Classification with Machine Learning in Python
2. What is Machine Learning?
INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: What is Machine Learning?
3. Python Data Science Environment
INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: Python Data Science Environment
4. For Mac Users
INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: For Mac Users
5. IPython in Browser
INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: IPython in Browser
6. Python Data Science Packages to Be Used
INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools: Python Data Science Packages to Be Used
2. Read in Data from Different Sources with Pandas

1. What are Pandas?
Read in Data from Different Sources with Pandas: What are Pandas?
2. Read in Data from CSV
Read in Data from Different Sources with Pandas: Read in Data from CSV
3. Read in Online CSV
Read in Data from Different Sources with Pandas: Read in Online CSV
4. Read in Excel Data
Read in Data from Different Sources with Pandas: Read in Excel Data
5. Read in HTML Data
Read in Data from Different Sources with Pandas: Read in HTML Data
6. Read in Data from Databases
Read in Data from Different Sources with Pandas: Read in Data from Databases
3. Data Cleaning & Munging

1. Remove Missing Values
Data Cleaning & Munging: Remove Missing Values
2. Conditional Data Selection
Data Cleaning & Munging: Conditional Data Selection
3. Data Grouping
Data Cleaning & Munging: Data Grouping
4. Data Sub setting
Data Cleaning & Munging: Data sub setting
5. Ranking & Sorting
Data Cleaning & Munging: Ranking & Sorting
6. Concatenate
Data Cleaning & Munging: Concatenate
7. Merging & Joining Data Frames
Data Cleaning & Munging: Merging & Joining Data Frames
4. Unsupervised Learning in Python

1. Unsupervised Classification- Some Basic Concepts
Unsupervised Learning in Python: Unsupervised Classification- Some Basic Concepts
2. K-Means Clustering: Theory
Unsupervised Learning in Python: K-Means Clustering: Theory
3. Implement K-Means on the Iris Data
Unsupervised Learning in Python: Implement K-Means on the Iris Data
4. Quantifying K-Means Clustering Performance
Unsupervised Learning in Python: Quantifying K-Means Clustering Performance
5. K-Means Clustering with Real Data
Unsupervised Learning in Python: K-Means Clustering with Real Data
6. How to Select the Optimal Number of Clusters?
Unsupervised Learning in Python: How to Select the Optimal Number of Clusters?
7. Gaussian Mixture Modelling (GMM)
Unsupervised Learning in Python: Gaussian Mixture Modelling (GMM)
8. Hierarchical Clustering-theory
Unsupervised Learning in Python: Hierarchical Clustering-theory
9. Hierarchical Clustering-practical
Unsupervised Learning in Python: Hierarchical Clustering-practical
5. Dimension Reduction & Feature Selection for Machine Learning

1. Principal Component Analysis (PCA)-Theory
Dimension Reduction & Feature Selection for Machine Learning: Principal Component Analysis (PCA)-Theory
2. Principal Component Analysis (PCA)-Case Study 1
Dimension Reduction & Feature Selection for Machine Learning: Principal Component Analysis (PCA)-Case Study 1
3. Principal Component Analysis (PCA)-Case Study 2
Dimension Reduction & Feature Selection for Machine Learning: Principal Component Analysis (PCA)-Case Study 2
4. Linear Discriminant Analysis (LDA) for Dimension Reduction
Dimension Reduction & Feature Selection for Machine Learning: Linear Discriminant Analysis (LDA) for Dimension Reduction
5. t-SNE Dimension Reduction
Dimension Reduction & Feature Selection for Machine Learning: t-SNE Dimension Reduction
6. Feature Selection to Select the Most Relevant Predictors
Dimension Reduction & Feature Selection for Machine Learning: Feature Selection to Select the Most Relevant Predictors
7. Recursive Feature Elimination (RFE)
Dimension Reduction & Feature Selection for Machine Learning: Recursive Feature Elimination (RFE)
6. Supervised Learning: Classification

1. Concepts Behind Supervised Learning
Supervised Learning: Classification: Concepts Behind Supervised Learning
2. Data Preparation for Supervised Learning
Supervised Learning: Classification: Data Preparation for Supervised Learning
3. Pointers on Evaluating the Accuracy of Classification Modelling
Supervised Learning: Classification: Pointers on Evaluating the Accuracy of Classification Modelling
4. Using Logistic Regression as a Classification Model
Supervised Learning: Classification: Using Logistic Regression as a Classification Model
5. kNN- Classification
Supervised Learning: Classification: kNN- Classification
6. Naive Bayes Classification
Supervised Learning: Classification: Naive Bayes Classification
7. Linear Discriminant Analysis
Supervised Learning: Classification: Linear Discriminant Analysis
8. SVM- Linear Classification
Supervised Learning: Classification: SVM- Linear Classification
9. Non-Linear SVM Classification
Supervised Learning: Classification: Non-Linear SVM Classification
10. RF-Classification
Supervised Learning: Classification: RF-Classification
11. Gradient Boosting Machine (GBM)
Supervised Learning: Classification: Gradient Boosting Machine (GBM)
12. Voting Classifier
Supervised Learning: Classification: Voting Classifier
7. Neural Networks and Deep Learning Based Classification Techniques

1. Perceptrons for Binary Classification
Neural Networks and Deep Learning Based Classification Techniques: Perceptrons for Binary Classification
2. Artificial Neural Networks (ANN) for Binary Classification
Neural Networks and Deep Learning Based Classification Techniques: Artificial Neural Networks (ANN) for Binary Classification
3. Multi-class Classification With MLP
Neural Networks and Deep Learning Based Classification Techniques: Multi-class Classification With MLP
4. Introduction to H20
Neural Networks and Deep Learning Based Classification Techniques: Introduction to H20
5. Use H20 for Deep Learning Classification
Neural Networks and Deep Learning Based Classification Techniques: Use H20 for Deep Learning Classification
6. H20 Deep Learning for Classification
Neural Networks and Deep Learning Based Classification Techniques: H20 Deep Learning for Classification

Packt

Python

Implement machine learning-based clustering and classification in Python for pattern recognition and data analysis

Clustering and Classification with Machine Learning in Python

General Admission

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">In the ever-evolving landscape of the business world, mastering management skills has become crucial for career success. The United Kingdom offers a myriad of opportunities for individuals aspiring to enhance their management capabilities and take their careers to new heights. This article explores the top management courses in the UK, guiding you on the path to success.</p><h2 fr-original-style="" style="box-sizing: border-box;">Understanding the Importance of Management Education</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="https://www.nativeassignmenthelp.co.uk/management-assignment-help" target="_blank" rel="noopener noreferrer" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Management assignment help</a> education equips individuals with the knowledge and skills necessary to lead organizations effectively. It fosters problem-solving, strategic thinking, and leadership abilities, making graduates highly sought after in various industries.</p><h2 fr-original-style="" style="box-sizing: border-box;">Exploring the Top Management Courses in the UK</h2><h3 id="isPasted" fr-original-style="" style="box-sizing: border-box;">Master of Business Administration (MBA)</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The MBA program is one of the most popular choices for management education. It provides a comprehensive understanding of various business aspects, including finance, marketing, and operations. Universities such as Oxford, Cambridge, and London Business School offer world-renowned MBA programs.</p><h3 fr-original-style="" style="box-sizing: border-box;">Master in Management (MiM)</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">MiM is designed for individuals at the early stages of their careers. It focuses on leadership and management fundamentals. Notable institutions offering MiM programs include LSE, Imperial College, and Warwick Business School.</p><h3 fr-original-style="" style="box-sizing: border-box;">Executive Education Programs</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">For professionals seeking to enhance their management skills while working, executive education programs offer a flexible solution. These programs are often delivered by top UK universities, allowing individuals to balance work and education effectively.</p><h2 id="isPasted" fr-original-style="" style="box-sizing: border-box;">Choosing the Right Management Course</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Selecting the right management course is a critical decision. Here are some factors to consider:</p><h3 fr-original-style="" style="box-sizing: border-box;">Career Goals and Aspirations</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Identify your career goals and how a specific management course aligns with them. Whether you aim to become an entrepreneur, a corporate leader, or a specialist in a particular field, your choice should reflect your aspirations.</p><h3 fr-original-style="" style="box-sizing: border-box;">Duration and Structure of the Course</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Different courses have varying durations and structures. MBA programs usually span one to two years, while MiM courses are typically shorter. Choose a program that fits your schedule and preferences.</p><h3 fr-original-style="" style="box-sizing: border-box;">Accreditation and Rankings</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Accreditation by reputable bodies and high global rankings are indicators of program quality. Check the accreditation and rankings of the courses you&#39;re interested in.</p><h3 fr-original-style="" style="box-sizing: border-box;">Location and Campus Facilities</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Consider the location of the university and the facilities it offers. Do you prefer a bustling city or a serene campus environment? Evaluate which setting suits your lifestyle and learning style.</p><h3 fr-original-style="" style="box-sizing: border-box;">Application and Admission Process</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Once you&#39;ve selected a course, the application and admission process is your next step. Be prepared to submit transcripts, letters of recommendation, and a personal statement. Each program may have specific requirements, so pay close attention to them.</p><h3 fr-original-style="" style="box-sizing: border-box;">Financial Considerations and Scholarships</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The cost of management education varies, with MBA programs generally being more expensive. However, many universities offer scholarships and financial aid. Research these options to alleviate your financial burden.</p><h3 fr-original-style="" style="box-sizing: border-box;">Career Opportunities After Graduation</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Management graduates are in high demand. Whether you pursue an MBA, MiM, or executive education, you can expect a wide range of career opportunities, including leadership roles, consulting positions, and entrepreneurship.</p><h3 fr-original-style="" style="box-sizing: border-box;">Success Stories: Alumni Achievements</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Many management program alumni have gone on to achieve great success. They lead multinational companies, drive innovation, and make a significant impact in their respective fields. These success stories are a testament to the quality of management education in the UK.</p><h3 fr-original-style="" style="box-sizing: border-box;">Testimonials from Students</h3><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Let&#39;s hear from the students who have embarked on this educational journey and achieved their career aspirations through top UK management courses.</p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Conclusion</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Mastering management is a journey filled with opportunities for growth and success. The United Kingdom&#39;s top management courses provide a solid foundation for aspiring leaders and entrepreneurs. With careful consideration and determination, you can navigate your way to a fulfilling and prosperous career in the world of management.</p>

In the ever-evolving landscape of the business world, mastering management skills has become crucial for career success. The United Kingdom offers a myriad of opportunities for individuals aspiring to enhance their management capabilities and take their careers to new heights. This article explores the top management courses in the UK, guiding you on the path to success.
Understanding the Importance of Management Education
Management assignment help education equips individuals with the knowledge and skills necessary to lead organizations effectively. It fosters problem-solving, strategic thinking, and leadership abilities, making graduates highly sought after in various industries.
Exploring the Top Management Courses in the UK
Master of Business Administration (MBA)
The MBA program is one of the most popular choices for management education. It provides a comprehensive understanding of various business aspects, including finance, marketing, and operations. Universities such as Oxford, Cambridge, and London Business School offer world-renowned MBA programs.
Master in Management (MiM)
MiM is designed for individuals at the early stages of their careers. It focuses on leadership and management fundamentals. Notable institutions offering MiM programs include LSE, Imperial College, and Warwick Business School.
Executive Education Programs
For professionals seeking to enhance their management skills while working, executive education programs offer a flexible solution. These programs are often delivered by top UK universities, allowing individuals to balance work and education effectively.
Choosing the Right Management Course
Selecting the right management course is a critical decision. Here are some factors to consider:
Career Goals and Aspirations
Identify your career goals and how a specific management course aligns with them. Whether you aim to become an entrepreneur, a corporate leader, or a specialist in a particular field, your choice should reflect your aspirations.
Duration and Structure of the Course
Different courses have varying durations and structures. MBA programs usually span one to two years, while MiM courses are typically shorter. Choose a program that fits your schedule and preferences.
Accreditation and Rankings
Accreditation by reputable bodies and high global rankings are indicators of program quality. Check the accreditation and rankings of the courses you're interested in.
Location and Campus Facilities
Consider the location of the university and the facilities it offers. Do you prefer a bustling city or a serene campus environment? Evaluate which setting suits your lifestyle and learning style.
Application and Admission Process
Once you've selected a course, the application and admission process is your next step. Be prepared to submit transcripts, letters of recommendation, and a personal statement. Each program may have specific requirements, so pay close attention to them.
Financial Considerations and Scholarships
The cost of management education varies, with MBA programs generally being more expensive. However, many universities offer scholarships and financial aid. Research these options to alleviate your financial burden.
Career Opportunities After Graduation
Management graduates are in high demand. Whether you pursue an MBA, MiM, or executive education, you can expect a wide range of career opportunities, including leadership roles, consulting positions, and entrepreneurship.
Success Stories: Alumni Achievements
Many management program alumni have gone on to achieve great success. They lead multinational companies, drive innovation, and make a significant impact in their respective fields. These success stories are a testament to the quality of management education in the UK.
Testimonials from Students
Let's hear from the students who have embarked on this educational journey and achieved their career aspirations through top UK management courses.
Conclusion
Mastering management is a journey filled with opportunities for growth and success. The United Kingdom's top management courses provide a solid foundation for aspiring leaders and entrepreneurs. With careful consideration and determination, you can navigate your way to a fulfilling and prosperous career in the world of management.

Assignment help Online

Get the best management assignment help and management course guide online by Uk management experts.

Mastering Management: Navigating the UK's Top Courses for Success

<strong>Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R</strong>
        <p>With so many R Statistics and Machine Learning courses around, why enroll for this?

Regression analysis is one of the central aspects of both Statistics and Machine Learning based analysis. This course will teach you Regression analysis for both Statistical data analysis and ML in R. It explores relevant concepts in a practical way, from basic to expert level. This course can help you achieve better grades, gain new analysis tools for your academic career, implement your knowledge in a work setting, and make business forecasting-related decisions. You will go all the way from implementing and inferring simple OLS (Ordinary Least Square) regression models to dealing with issues of multicollinearity in regression to ML based regression models.

Become a Regression analysis expert and harness the power of R for your analysis

&bull; Get started with R and RStudio. Install these on your system, learn to load packages, and read in different types of data in R
&bull; Carry out data cleaning and data visualization using R
&bull; Implement Ordinary Least Square (OLS) regression in R and learn how to interpret the results.
&bull; Learn how to deal with multicollinearity both through the variable selection and regularization techniques such as ridge regression
&bull; Carry out variable and regression model selection using both statistical and machine learning techniques, including using cross-validation methods.
&bull; Evaluate the regression model accuracy
&bull; Implement Generalized Linear Models (GLMs) such as logistic regression and Poisson regression. Use logistic regression as a binary classifier to distinguish between male and female voices.
&bull; Use non-parametric techniques such as Generalized Additive Models (GAMs) to work with non-linear and non-parametric data.
&bull; Work with tree-based ML models

All the code and supporting files for this course are available at - https://github.com/PacktPublishing/Regression-Analysis-for-Statistics-and-Machine-Learning-in-R</p>
        <h2>What You Will Learn</h2><p>Implement and infer Ordinary Least Square (OLS) regression using R<br>Apply statistical and ML based regression models to deal with problems such as multicollinearity<br>Carry out the variable selection and assess model accuracy using techniques such as cross-validation<br>Implement and infer Generalized Linear Models (GLMs), including using logistic regression as a binary classifier</p>
        <h2>Audience</h2><p>This course is for students interested in getting started with data science applications in the RStudio environment. Students wishing to learn to implement statistical modeling techniques for regression analysis on real data. Anyone with prior exposure to R who wants to get started with practical data science.</p>
        <h2>Approach</h2><p>This is a practical, hands-on course. We will spend some time dealing with some theoretical concepts related to both statistical and machine learning regression analysis. However, the majority of the course will focus on implementing different techniques on real data and interpreting the results. After each video, you will learn a new concept or technique which you can apply to your own projects.</p>
        <h2>Key Features</h2><p>Provided practical indepth training for you to get started with R * Perform some of the most common advanced regression analysis-based techniques * Use R to perform different statistical and machine learning data analysis and visualization tasks</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/regression-analysis-for-statistics-and-machine-learning-in-r</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Get Started with Practical Regression Analysis in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools</p></td></tr><tr><td style='padding: 15px;'><p>2. Difference Between Statistical Analysis & Machine Learning</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Difference Between Statistical Analysis &amp; Machine Learning</p></td></tr><tr><td style='padding: 15px;'><p>3. Getting Started with R and R Studio</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Getting Started with R and R Studio</p></td></tr><tr><td style='padding: 15px;'><p>4. Reading in Data with R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Reading in Data with R</p></td></tr><tr><td style='padding: 15px;'><p>5. Data Cleaning with R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Data Cleaning with R</p></td></tr><tr><td style='padding: 15px;'><p>6. Some More Data Cleaning with R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Some More Data Cleaning with R</p></td></tr><tr><td style='padding: 15px;'><p>7. Basic Exploratory Data Analysis in R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Basic Exploratory Data Analysis in R</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusion to Section 1</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Conclusion to Section 1</p></td></tr></tbody></table><br><h4>2. Ordinary Least Square Regression Modelling</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. OLS Regression- Theory</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: OLS Regression- Theory</p></td></tr><tr><td style='padding: 15px;'><p>2. OLS-Implementation</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: OLS-Implementation</p></td></tr><tr><td style='padding: 15px;'><p>3. More on Result Interpretations</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: More on Result Interpretations</p></td></tr><tr><td style='padding: 15px;'><p>4. Confidence Interval-Theory</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Confidence Interval-Theory</p></td></tr><tr><td style='padding: 15px;'><p>5. Calculate the Confidence Interval in R</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Calculate the Confidence Interval in R</p></td></tr><tr><td style='padding: 15px;'><p>6. Confidence Interval and OLS Regressions</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Confidence Interval and OLS Regressions</p></td></tr><tr><td style='padding: 15px;'><p>7. Linear Regression without Intercept</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Linear Regression without Intercept</p></td></tr><tr><td style='padding: 15px;'><p>8. Implement ANOVA on OLS Regression</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Implement ANOVA on OLS Regression</p></td></tr><tr><td style='padding: 15px;'><p>9. Multiple Linear Regression</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Multiple Linear Regression</p></td></tr><tr><td style='padding: 15px;'><p>10. Multiple Linear regression with Interaction and Dummy Variables</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Multiple Linear regression with Interaction and Dummy Variables</p></td></tr><tr><td style='padding: 15px;'><p>11. Some Basic Conditions that OLS Models Have to Fulfill</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Some Basic Conditions that OLS Models Have to Fulfill</p></td></tr><tr><td style='padding: 15px;'><p>12. Conclusions to Section 2</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Conclusions to Section 2</p></td></tr></tbody></table><br><h4>3. Deal with Multicollinearity in OLS Regression Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Identify Multicollinearity</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Identify Multicollinearity</p></td></tr><tr><td style='padding: 15px;'><p>2. Doing Regression Analyses with Correlated Predictor Variables</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Doing Regression Analyses with Correlated Predictor Variables</p></td></tr><tr><td style='padding: 15px;'><p>3. Principal Component Regression in R</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Principal Component Regression in R</p></td></tr><tr><td style='padding: 15px;'><p>4. Partial Least Square Regression in R</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Partial Least Square Regression in R</p></td></tr><tr><td style='padding: 15px;'><p>5. Ridge Regression in R</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Ridge Regression in R</p></td></tr><tr><td style='padding: 15px;'><p>6. LASSO Regression</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: LASSO Regression</p></td></tr><tr><td style='padding: 15px;'><p>7. Conclusion to Section 3</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Conclusion to Section 3</p></td></tr></tbody></table><br><h4>4. Variable & Model Selection</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Why Do Any Kind of Selection?</p><p style='margin: 0'>Variable &amp; Model Selection: Why Do Any Kind of Selection?</p></td></tr><tr><td style='padding: 15px;'><p>2. Select the Most Suitable OLS Regression Model</p><p style='margin: 0'>Variable &amp; Model Selection: Select the Most Suitable OLS Regression Model</p></td></tr><tr><td style='padding: 15px;'><p>3. Select Model Subsets</p><p style='margin: 0'>Variable &amp; Model Selection: Select Model Subsets</p></td></tr><tr><td style='padding: 15px;'><p>4. Machine Learning Perspective on Evaluate Regression Model Accuracy</p><p style='margin: 0'>Variable &amp; Model Selection: Machine Learning Perspective on Evaluate Regression Model Accuracy</p></td></tr><tr><td style='padding: 15px;'><p>5. Evaluate Regression Model Performance</p><p style='margin: 0'>Variable &amp; Model Selection: Evaluate Regression Model Performance</p></td></tr><tr><td style='padding: 15px;'><p>6. LASSO Regression for Variable Selection</p><p style='margin: 0'>Variable &amp; Model Selection: LASSO Regression for Variable Selection</p></td></tr><tr><td style='padding: 15px;'><p>7. Identify the Contribution of Predictors in Explaining the Variation in Y</p><p style='margin: 0'>Variable &amp; Model Selection: Identify the Contribution of Predictors in Explaining the Variation in Y</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusions to Section 4</p><p style='margin: 0'>Variable &amp; Model Selection: Conclusions to Section 4</p></td></tr></tbody></table><br><h4>5. Dealing with Other Violations of the OLS Regression Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Transformations</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Data Transformations</p></td></tr><tr><td style='padding: 15px;'><p>2. Robust Regression-Deal with Outliers</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Robust Regression-Deal with Outliers</p></td></tr><tr><td style='padding: 15px;'><p>3. Dealing with Heteroscedasticity</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Dealing with Heteroscedasticity</p></td></tr><tr><td style='padding: 15px;'><p>4. Conclusions to Section 5</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Conclusions to Section 5</p></td></tr></tbody></table><br><h4>6. Generalized Linear Models (GLMs)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What are GLMs?</p><p style='margin: 0'>Generalized Linear Models (GLMs): What are GLMs?</p></td></tr><tr><td style='padding: 15px;'><p>2. Logistic regression</p><p style='margin: 0'>Generalized Linear Models (GLMs): Logistic regression</p></td></tr><tr><td style='padding: 15px;'><p>3. Logistic Regression for Binary Response Variable</p><p style='margin: 0'>Generalized Linear Models (GLMs): Logistic Regression for Binary Response Variable</p></td></tr><tr><td style='padding: 15px;'><p>4. Multinomial Logistic Regression</p><p style='margin: 0'>Generalized Linear Models (GLMs): Multinomial Logistic Regression</p></td></tr><tr><td style='padding: 15px;'><p>5. Regression for Count Data</p><p style='margin: 0'>Generalized Linear Models (GLMs): Regression for Count Data</p></td></tr><tr><td style='padding: 15px;'><p>6. Goodness of fit testing</p><p style='margin: 0'>Generalized Linear Models (GLMs): Goodness of fit testing</p></td></tr><tr><td style='padding: 15px;'><p>7. Conclusions to Section 6</p><p style='margin: 0'>Generalized Linear Models (GLMs): Conclusions to Section 6</p></td></tr></tbody></table><br><h4>7. Working with Non-Parametric and Non-Linear Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Polynomial and Non-linear regression</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Polynomial and Non-linear regression</p></td></tr><tr><td style='padding: 15px;'><p>2. Generalized Additive Models (GAMs) in R</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Generalized Additive Models (GAMs) in R</p></td></tr><tr><td style='padding: 15px;'><p>3. Boosted GAM Regression</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Boosted GAM Regression</p></td></tr><tr><td style='padding: 15px;'><p>4. Multivariate Adaptive Regression Splines (MARS)</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Multivariate Adaptive Regression Splines (MARS)</p></td></tr><tr><td style='padding: 15px;'><p>5. CART-Regression Trees in R</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: CART-Regression Trees in R</p></td></tr><tr><td style='padding: 15px;'><p>6. Conditional Inference Trees</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Conditional Inference Trees</p></td></tr><tr><td style='padding: 15px;'><p>7. Random Forest(RF)</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Random Forest(RF)</p></td></tr><tr><td style='padding: 15px;'><p>8. Gradient Boosting Regression</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Gradient Boosting Regression</p></td></tr><tr><td style='padding: 15px;'><p>9. ML Model Selection</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: ML Model Selection</p></td></tr><tr><td style='padding: 15px;'><p>10. Conclusions to Section 7</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Conclusions to Section 7</p></td></tr></tbody></table>

Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R
With so many R Statistics and Machine Learning courses around, why enroll for this? Regression analysis is one of the central aspects of both Statistics and Machine Learning based analysis. This course will teach you Regression analysis for both Statistical data analysis and ML in R. It explores relevant concepts in a practical way, from basic to expert level. This course can help you achieve better grades, gain new analysis tools for your academic career, implement your knowledge in a work setting, and make business forecasting-related decisions. You will go all the way from implementing and inferring simple OLS (Ordinary Least Square) regression models to dealing with issues of multicollinearity in regression to ML based regression models. Become a Regression analysis expert and harness the power of R for your analysis • Get started with R and RStudio. Install these on your system, learn to load packages, and read in different types of data in R
• Carry out data cleaning and data visualization using R
• Implement Ordinary Least Square (OLS) regression in R and learn how to interpret the results.
• Learn how to deal with multicollinearity both through the variable selection and regularization techniques such as ridge regression
• Carry out variable and regression model selection using both statistical and machine learning techniques, including using cross-validation methods.
• Evaluate the regression model accuracy
• Implement Generalized Linear Models (GLMs) such as logistic regression and Poisson regression. Use logistic regression as a binary classifier to distinguish between male and female voices.
• Use non-parametric techniques such as Generalized Additive Models (GAMs) to work with non-linear and non-parametric data.
• Work with tree-based ML models All the code and supporting files for this course are available at - https://github.com/PacktPublishing/Regression-Analysis-for-Statistics-and-Machine-Learning-in-R
What You Will Learn
Implement and infer Ordinary Least Square (OLS) regression using R
Apply statistical and ML based regression models to deal with problems such as multicollinearity
Carry out the variable selection and assess model accuracy using techniques such as cross-validation
Implement and infer Generalized Linear Models (GLMs), including using logistic regression as a binary classifier
Audience
This course is for students interested in getting started with data science applications in the RStudio environment. Students wishing to learn to implement statistical modeling techniques for regression analysis on real data. Anyone with prior exposure to R who wants to get started with practical data science.
Approach
This is a practical, hands-on course. We will spend some time dealing with some theoretical concepts related to both statistical and machine learning regression analysis. However, the majority of the course will focus on implementing different techniques on real data and interpreting the results. After each video, you will learn a new concept or technique which you can apply to your own projects.
Key Features
Provided practical indepth training for you to get started with R * Perform some of the most common advanced regression analysis-based techniques * Use R to perform different statistical and machine learning data analysis and visualization tasks
Github Repo
https://github.com/packtpublishing/regression-analysis-for-statistics-and-machine-learning-in-r
About the Author
Minerva Singh
Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.
Course Outline
1. Get Started with Practical Regression Analysis in R

1. INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools
Get Started with Practical Regression Analysis in R: INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools
2. Difference Between Statistical Analysis & Machine Learning
Get Started with Practical Regression Analysis in R: Difference Between Statistical Analysis & Machine Learning
3. Getting Started with R and R Studio
Get Started with Practical Regression Analysis in R: Getting Started with R and R Studio
4. Reading in Data with R
Get Started with Practical Regression Analysis in R: Reading in Data with R
5. Data Cleaning with R
Get Started with Practical Regression Analysis in R: Data Cleaning with R
6. Some More Data Cleaning with R
Get Started with Practical Regression Analysis in R: Some More Data Cleaning with R
7. Basic Exploratory Data Analysis in R
Get Started with Practical Regression Analysis in R: Basic Exploratory Data Analysis in R
8. Conclusion to Section 1
Get Started with Practical Regression Analysis in R: Conclusion to Section 1
2. Ordinary Least Square Regression Modelling

1. OLS Regression- Theory
Ordinary Least Square Regression Modelling: OLS Regression- Theory
2. OLS-Implementation
Ordinary Least Square Regression Modelling: OLS-Implementation
3. More on Result Interpretations
Ordinary Least Square Regression Modelling: More on Result Interpretations
4. Confidence Interval-Theory
Ordinary Least Square Regression Modelling: Confidence Interval-Theory
5. Calculate the Confidence Interval in R
Ordinary Least Square Regression Modelling: Calculate the Confidence Interval in R
6. Confidence Interval and OLS Regressions
Ordinary Least Square Regression Modelling: Confidence Interval and OLS Regressions
7. Linear Regression without Intercept
Ordinary Least Square Regression Modelling: Linear Regression without Intercept
8. Implement ANOVA on OLS Regression
Ordinary Least Square Regression Modelling: Implement ANOVA on OLS Regression
9. Multiple Linear Regression
Ordinary Least Square Regression Modelling: Multiple Linear Regression
10. Multiple Linear regression with Interaction and Dummy Variables
Ordinary Least Square Regression Modelling: Multiple Linear regression with Interaction and Dummy Variables
11. Some Basic Conditions that OLS Models Have to Fulfill
Ordinary Least Square Regression Modelling: Some Basic Conditions that OLS Models Have to Fulfill
12. Conclusions to Section 2
Ordinary Least Square Regression Modelling: Conclusions to Section 2
3. Deal with Multicollinearity in OLS Regression Models

1. Identify Multicollinearity
Deal with Multicollinearity in OLS Regression Models: Identify Multicollinearity
2. Doing Regression Analyses with Correlated Predictor Variables
Deal with Multicollinearity in OLS Regression Models: Doing Regression Analyses with Correlated Predictor Variables
3. Principal Component Regression in R
Deal with Multicollinearity in OLS Regression Models: Principal Component Regression in R
4. Partial Least Square Regression in R
Deal with Multicollinearity in OLS Regression Models: Partial Least Square Regression in R
5. Ridge Regression in R
Deal with Multicollinearity in OLS Regression Models: Ridge Regression in R
6. LASSO Regression
Deal with Multicollinearity in OLS Regression Models: LASSO Regression
7. Conclusion to Section 3
Deal with Multicollinearity in OLS Regression Models: Conclusion to Section 3
4. Variable & Model Selection

1. Why Do Any Kind of Selection?
Variable & Model Selection: Why Do Any Kind of Selection?
2. Select the Most Suitable OLS Regression Model
Variable & Model Selection: Select the Most Suitable OLS Regression Model
3. Select Model Subsets
Variable & Model Selection: Select Model Subsets
4. Machine Learning Perspective on Evaluate Regression Model Accuracy
Variable & Model Selection: Machine Learning Perspective on Evaluate Regression Model Accuracy
5. Evaluate Regression Model Performance
Variable & Model Selection: Evaluate Regression Model Performance
6. LASSO Regression for Variable Selection
Variable & Model Selection: LASSO Regression for Variable Selection
7. Identify the Contribution of Predictors in Explaining the Variation in Y
Variable & Model Selection: Identify the Contribution of Predictors in Explaining the Variation in Y
8. Conclusions to Section 4
Variable & Model Selection: Conclusions to Section 4
5. Dealing with Other Violations of the OLS Regression Models

1. Data Transformations
Dealing with Other Violations of the OLS Regression Models: Data Transformations
2. Robust Regression-Deal with Outliers
Dealing with Other Violations of the OLS Regression Models: Robust Regression-Deal with Outliers
3. Dealing with Heteroscedasticity
Dealing with Other Violations of the OLS Regression Models: Dealing with Heteroscedasticity
4. Conclusions to Section 5
Dealing with Other Violations of the OLS Regression Models: Conclusions to Section 5
6. Generalized Linear Models (GLMs)

1. What are GLMs?
Generalized Linear Models (GLMs): What are GLMs?
2. Logistic regression
Generalized Linear Models (GLMs): Logistic regression
3. Logistic Regression for Binary Response Variable
Generalized Linear Models (GLMs): Logistic Regression for Binary Response Variable
4. Multinomial Logistic Regression
Generalized Linear Models (GLMs): Multinomial Logistic Regression
5. Regression for Count Data
Generalized Linear Models (GLMs): Regression for Count Data
6. Goodness of fit testing
Generalized Linear Models (GLMs): Goodness of fit testing
7. Conclusions to Section 6
Generalized Linear Models (GLMs): Conclusions to Section 6
7. Working with Non-Parametric and Non-Linear Data

1. Polynomial and Non-linear regression
Working with Non-Parametric and Non-Linear Data: Polynomial and Non-linear regression
2. Generalized Additive Models (GAMs) in R
Working with Non-Parametric and Non-Linear Data: Generalized Additive Models (GAMs) in R
3. Boosted GAM Regression
Working with Non-Parametric and Non-Linear Data: Boosted GAM Regression
4. Multivariate Adaptive Regression Splines (MARS)
Working with Non-Parametric and Non-Linear Data: Multivariate Adaptive Regression Splines (MARS)
5. CART-Regression Trees in R
Working with Non-Parametric and Non-Linear Data: CART-Regression Trees in R
6. Conditional Inference Trees
Working with Non-Parametric and Non-Linear Data: Conditional Inference Trees
7. Random Forest(RF)
Working with Non-Parametric and Non-Linear Data: Random Forest(RF)
8. Gradient Boosting Regression
Working with Non-Parametric and Non-Linear Data: Gradient Boosting Regression
9. ML Model Selection
Working with Non-Parametric and Non-Linear Data: ML Model Selection
10. Conclusions to Section 7
Working with Non-Parametric and Non-Linear Data: Conclusions to Section 7

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Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R

Regression Analysis for Statistics & Machine Learning in R

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Module 1: Proofreading Basics			
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Computing & IT

Discover the power of proofreading AI tools like Grammarly and ProWritingAid. Master your skills in editing and proofreading for any legal or official document.

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<strong>The underlying patterns in your data hold vital insights; unearth them with cutting-edge clustering and classification techniques in R</strong>
        <p>This course is your complete guide to both supervised and unsupervised learning using R. This course covers all the main aspects of practical data science; if you take this course, there is no need to take other courses or buy books on R-based data science. In this age of big data, companies across the Globe use R to sift through the avalanche of information at their disposal. By becoming proficient in unsupervised and supervised learning in R, you can give your company a competitive edge and take your career to the next level.

Over the course of research, the author realized that almost all the R data science courses and books out there do take account of the multidimensional nature of the topic. This course will give you a robust grounding in the main aspects of machine learning: clustering and classification. Unlike other R instructors, the author digs deep into R's machine learning features and give you a one-of-a-kind grounding in data science! You will go all the way from carrying out data reading & cleaning to machine learning, to finally implementing powerful machine learning algorithms and evaluating their performance via R.
The following topics will be covered: - 
&bull; A full introduction to the R Framework for data science 
&bull; Data structures and reading in R, including CSV, Excel, and HTML data 
&bull; How to pre-process and clean data by removing NAs/No data, visualization 
&bull; Machine learning, supervised learning, and unsupervised learning in R 
&bull; Model building and selection and much more!

The course will help you implement methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R-based data science in real life. After taking this course, you'll easily use data science packages such as Caret to work with real data in R. You'll even understand concepts such as unsupervised learning, dimension reduction, and supervised learning. 

All the code and supporting files for this course are available at - https://github.com/PacktPublishing/Clustering-and-Classification-with-Machine-Learning-in-R</p>
        <h2>What You Will Learn</h2><p>Read-in data into the R environment from different sources<br>Carry out basic data pre-processing and wrangling in R Studio<br>Implement unsupervised/clustering techniques such as K-means clustering<br>Implement dimensional reduction techniques (PCA) and feature selection<br>Implement supervised learning techniques/classification such as Random Forests<br>Evaluate model performance and learn the best practices for evaluating machine learning model accuracy</p>
        <h2>Audience</h2><p>This course is for students interested in getting started with data science applications in the R Studio environment. Students wishing to learn how to implement unsupervised learning on real data. Anyone with prior exposure to R who wants to get started with practical data science.</p>
        <h2>Approach</h2><p>Every video is packed with hands-on instructions and clear explanations. Real data has been used to demonstrate how to implement these techniques in real life, on your data.</p>
        <h2>Key Features</h2><p>Provides in-depth training in everything you need to know to get started with practical R data science * Jargon-free and suitable for people who have a non-mathematical background * In-depth coverage of the latest unsupervised and supervised techniques </p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/clustering-and-classification-with-machine-learning-in-r</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Introduction to the Course</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Welcome to Clustering & Classification with Machine Learning in R</p><p style='margin: 0'>Introduction to the Course: Welcome to Clustering & Classification with Machine Learning in R</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing R and R Studio</p><p style='margin: 0'>Introduction to the Course: Installing R and R Studio</p></td></tr></tbody></table><br><h4>2. Read in Data from Different Sources in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Read in CSV & Excel Data</p><p style='margin: 0'>Read in Data from Different Sources in R: Read in CSV & Excel Data</p></td></tr><tr><td style='padding: 15px;'><p>2. Read in Unzipped Folder</p><p style='margin: 0'>Read in Data from Different Sources in R: Read in Unzipped Folder</p></td></tr><tr><td style='padding: 15px;'><p>3. Read in Online CSV</p><p style='margin: 0'>Read in Data from Different Sources in R: Read in Online CSV</p></td></tr><tr><td style='padding: 15px;'><p>4. Read in Googlesheets</p><p style='margin: 0'>Read in Data from Different Sources in R: Read in Googlesheets</p></td></tr><tr><td style='padding: 15px;'><p>5. Read in Data from Online HTML Tables-Part 1</p><p style='margin: 0'>Read in Data from Different Sources in R: Read in Data from Online HTML Tables-Part 1</p></td></tr><tr><td style='padding: 15px;'><p>6. Read in Data from Online HTML Tables-Part 2</p><p style='margin: 0'>Read in Data from Different Sources in R: Read in Data from Online HTML Tables-Part 2</p></td></tr><tr><td style='padding: 15px;'><p>7. Read Data from a Database</p><p style='margin: 0'>Read in Data from Different Sources in R: Read Data from a Database</p></td></tr></tbody></table><br><h4>3. Data Pre-processing and Visualization</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Remove Missing Values</p><p style='margin: 0'>Data Pre-processing and Visualization: Remove Missing Values</p></td></tr><tr><td style='padding: 15px;'><p>2. More Data Cleaning</p><p style='margin: 0'>Data Pre-processing and Visualization: More Data Cleaning</p></td></tr><tr><td style='padding: 15px;'><p>3. Introduction to dplyr for Data Summarizing-Part 1</p><p style='margin: 0'>Data Pre-processing and Visualization: Introduction to dplyr for Data Summarizing-Part 1</p></td></tr><tr><td style='padding: 15px;'><p>4. Introduction to dplyr for Data Summarizing-Part 2</p><p style='margin: 0'>Data Pre-processing and Visualization: Introduction to dplyr for Data Summarizing-Part 2</p></td></tr><tr><td style='padding: 15px;'><p>5. Exploratory Data Analysis (EDA): Basic Visualizations with R</p><p style='margin: 0'>Data Pre-processing and Visualization: Exploratory Data Analysis (EDA): Basic Visualizations with R</p></td></tr><tr><td style='padding: 15px;'><p>6. More Exploratory Data Analysis with xda</p><p style='margin: 0'>Data Pre-processing and Visualization: More Exploratory Data Analysis with xda</p></td></tr><tr><td style='padding: 15px;'><p>7. Data Exploration & Visualization With dplyr & ggplot2</p><p style='margin: 0'>Data Pre-processing and Visualization: Data Exploration & Visualization With dplyr & ggplot2</p></td></tr><tr><td style='padding: 15px;'><p>8. Associations Between Quantitative Variables- Theory</p><p style='margin: 0'>Data Pre-processing and Visualization: Associations Between Quantitative Variables- Theory</p></td></tr><tr><td style='padding: 15px;'><p>9. Testing for Correlation</p><p style='margin: 0'>Data Pre-processing and Visualization: Testing for Correlation</p></td></tr><tr><td style='padding: 15px;'><p>10. Evaluate the Relation Between Nominal Variables</p><p style='margin: 0'>Data Pre-processing and Visualization: Evaluate the Relation Between Nominal Variables</p></td></tr><tr><td style='padding: 15px;'><p>11. Cramer's V for Examining the Strength of Association Between Nominal Variable</p><p style='margin: 0'>Data Pre-processing and Visualization: Cramer's V for Examining the Strength of Association Between Nominal Variable</p></td></tr></tbody></table><br><h4>4. Machine Learning for Data Science</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. How is Machine Learning Different from Statistical Data Analysis?</p><p style='margin: 0'>Machine Learning for Data Science: How is Machine Learning Different from Statistical Data Analysis?</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Machine Learning (ML) About? Some Theoretical Pointers</p><p style='margin: 0'>Machine Learning for Data Science: What is Machine Learning (ML) About? Some Theoretical Pointers</p></td></tr></tbody></table><br><h4>5. Unsupervised Learning in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. K-Means Clustering</p><p style='margin: 0'>Unsupervised Learning in R: K-Means Clustering</p></td></tr><tr><td style='padding: 15px;'><p>2. Other Ways of Selecting Cluster Numbers</p><p style='margin: 0'>Unsupervised Learning in R: Other Ways of Selecting Cluster Numbers</p></td></tr><tr><td style='padding: 15px;'><p>3. Fuzzy K-Means Clustering</p><p style='margin: 0'>Unsupervised Learning in R: Fuzzy K-Means Clustering</p></td></tr><tr><td style='padding: 15px;'><p>4. Weighted k-means</p><p style='margin: 0'>Unsupervised Learning in R: Weighted k-means</p></td></tr><tr><td style='padding: 15px;'><p>5. Partitioning Around Meloids (PAM)</p><p style='margin: 0'>Unsupervised Learning in R: Partitioning Around Meloids (PAM)</p></td></tr><tr><td style='padding: 15px;'><p>6. Hierarchical Clustering in R</p><p style='margin: 0'>Unsupervised Learning in R: Hierarchical Clustering in R</p></td></tr><tr><td style='padding: 15px;'><p>7. Expectation-Maximization (EM) in R</p><p style='margin: 0'>Unsupervised Learning in R: Expectation-Maximization (EM) in R</p></td></tr><tr><td style='padding: 15px;'><p>8. DBSCAN Clustering in R</p><p style='margin: 0'>Unsupervised Learning in R: DBSCAN Clustering in R</p></td></tr><tr><td style='padding: 15px;'><p>9. Cluster a Mixed Dataset</p><p style='margin: 0'>Unsupervised Learning in R: Cluster a Mixed Dataset</p></td></tr><tr><td style='padding: 15px;'><p>10. Should We Even Do Clustering?</p><p style='margin: 0'>Unsupervised Learning in R: Should We Even Do Clustering?</p></td></tr><tr><td style='padding: 15px;'><p>11. Assess Clustering Performance</p><p style='margin: 0'>Unsupervised Learning in R: Assess Clustering Performance</p></td></tr><tr><td style='padding: 15px;'><p>12. Which Clustering Algorithm to Choose?</p><p style='margin: 0'>Unsupervised Learning in R: Which Clustering Algorithm to Choose?</p></td></tr></tbody></table><br><h4>6. Feature/Dimension Reduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Dimension Reduction-theory</p><p style='margin: 0'>Feature/Dimension Reduction: Dimension Reduction-theory</p></td></tr><tr><td style='padding: 15px;'><p>2. Principal Component Analysis (PCA)</p><p style='margin: 0'>Feature/Dimension Reduction: Principal Component Analysis (PCA)</p></td></tr><tr><td style='padding: 15px;'><p>3. More on PCA</p><p style='margin: 0'>Feature/Dimension Reduction: More on PCA</p></td></tr><tr><td style='padding: 15px;'><p>4. Multidimensional Scaling</p><p style='margin: 0'>Feature/Dimension Reduction: Multidimensional Scaling</p></td></tr><tr><td style='padding: 15px;'><p>5. Singular Value Decomposition (SVD)</p><p style='margin: 0'>Feature/Dimension Reduction: Singular Value Decomposition (SVD)</p></td></tr></tbody></table><br><h4>7. Feature Selection to Select the Most Relevant Predictors</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Removing Highly Correlated Predictor Variables</p><p style='margin: 0'>Feature Selection to Select the Most Relevant Predictors: Removing Highly Correlated Predictor Variables</p></td></tr><tr><td style='padding: 15px;'><p>2. Variable Selection Using LASSO Regression</p><p style='margin: 0'>Feature Selection to Select the Most Relevant Predictors: Variable Selection Using LASSO Regression</p></td></tr><tr><td style='padding: 15px;'><p>3. Variable Selection with FSelector</p><p style='margin: 0'>Feature Selection to Select the Most Relevant Predictors: Variable Selection with FSelector</p></td></tr><tr><td style='padding: 15px;'><p>4. Boruta Analysis for Feature Selection</p><p style='margin: 0'>Feature Selection to Select the Most Relevant Predictors: Boruta Analysis for Feature Selection</p></td></tr></tbody></table><br><h4>8. Supervised Learning Theory</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Some Basic Supervised Learning Concepts</p><p style='margin: 0'>Supervised Learning Theory: Some Basic Supervised Learning Concepts</p></td></tr><tr><td style='padding: 15px;'><p>2. Pre-processing for Supervised Learning</p><p style='margin: 0'>Supervised Learning Theory: Pre-processing for Supervised Learning</p></td></tr></tbody></table><br><h4>9. Supervised Learning: Classification</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What are GLMs?</p><p style='margin: 0'>Supervised Learning: Classification: What are GLMs?</p></td></tr><tr><td style='padding: 15px;'><p>2. Logistic Regression Models as Binary Classifiers</p><p style='margin: 0'>Supervised Learning: Classification: Logistic Regression Models as Binary Classifiers</p></td></tr><tr><td style='padding: 15px;'><p>3. Binary Classifier with PCA</p><p style='margin: 0'>Supervised Learning: Classification: Binary Classifier with PCA</p></td></tr><tr><td style='padding: 15px;'><p>4. Some Pointers on Evaluating Accuracy</p><p style='margin: 0'>Supervised Learning: Classification: Some Pointers on Evaluating Accuracy</p></td></tr><tr><td style='padding: 15px;'><p>5. Obtain Binary Classification Accuracy Metrics</p><p style='margin: 0'>Supervised Learning: Classification: Obtain Binary Classification Accuracy Metrics</p></td></tr><tr><td style='padding: 15px;'><p>6. More on Binary Accuracy Measures</p><p style='margin: 0'>Supervised Learning: Classification: More on Binary Accuracy Measures</p></td></tr><tr><td style='padding: 15px;'><p>7. Linear Discriminant Analysis</p><p style='margin: 0'>Supervised Learning: Classification: Linear Discriminant Analysis</p></td></tr><tr><td style='padding: 15px;'><p>8. Our Multi-class Classification Problem</p><p style='margin: 0'>Supervised Learning: Classification: Our Multi-class Classification Problem</p></td></tr><tr><td style='padding: 15px;'><p>9. Classification Trees</p><p style='margin: 0'>Supervised Learning: Classification: Classification Trees</p></td></tr><tr><td style='padding: 15px;'><p>10. More on Classification Tree Visualization</p><p style='margin: 0'>Supervised Learning: Classification: More on Classification Tree Visualization</p></td></tr><tr><td style='padding: 15px;'><p>11. Classification with Party Package</p><p style='margin: 0'>Supervised Learning: Classification: Classification with Party Package</p></td></tr><tr><td style='padding: 15px;'><p>12. Decision Trees</p><p style='margin: 0'>Supervised Learning: Classification: Decision Trees</p></td></tr><tr><td style='padding: 15px;'><p>13. Random Forest (RF) Classification</p><p style='margin: 0'>Supervised Learning: Classification: Random Forest (RF) Classification</p></td></tr><tr><td style='padding: 15px;'><p>14. Examine Individual Variable Importance for Random Forests</p><p style='margin: 0'>Supervised Learning: Classification: Examine Individual Variable Importance for Random Forests</p></td></tr><tr><td style='padding: 15px;'><p>15. GBM Classification</p><p style='margin: 0'>Supervised Learning: Classification: GBM Classification</p></td></tr><tr><td style='padding: 15px;'><p>16. Support Vector Machines (SVM) for Classification</p><p style='margin: 0'>Supervised Learning: Classification: Support Vector Machines (SVM) for Classification</p></td></tr><tr><td style='padding: 15px;'><p>17. More SVM for Classification</p><p style='margin: 0'>Supervised Learning: Classification: More SVM for Classification</p></td></tr><tr><td style='padding: 15px;'><p>18. Variable Importance in SVM Modelling with rminer</p><p style='margin: 0'>Supervised Learning: Classification: Variable Importance in SVM Modelling with rminer</p></td></tr></tbody></table><br><h4>10. Additional Lectures</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Fuzzy C-Means Clustering</p><p style='margin: 0'>Additional Lectures: Fuzzy C-Means Clustering</p></td></tr></tbody></table>

The underlying patterns in your data hold vital insights; unearth them with cutting-edge clustering and classification techniques in R
This course is your complete guide to both supervised and unsupervised learning using R. This course covers all the main aspects of practical data science; if you take this course, there is no need to take other courses or buy books on R-based data science. In this age of big data, companies across the Globe use R to sift through the avalanche of information at their disposal. By becoming proficient in unsupervised and supervised learning in R, you can give your company a competitive edge and take your career to the next level. Over the course of research, the author realized that almost all the R data science courses and books out there do take account of the multidimensional nature of the topic. This course will give you a robust grounding in the main aspects of machine learning: clustering and classification. Unlike other R instructors, the author digs deep into R's machine learning features and give you a one-of-a-kind grounding in data science! You will go all the way from carrying out data reading & cleaning to machine learning, to finally implementing powerful machine learning algorithms and evaluating their performance via R.
The following topics will be covered: - • A full introduction to the R Framework for data science • Data structures and reading in R, including CSV, Excel, and HTML data • How to pre-process and clean data by removing NAs/No data, visualization • Machine learning, supervised learning, and unsupervised learning in R • Model building and selection and much more! The course will help you implement methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R-based data science in real life. After taking this course, you'll easily use data science packages such as Caret to work with real data in R. You'll even understand concepts such as unsupervised learning, dimension reduction, and supervised learning. All the code and supporting files for this course are available at - https://github.com/PacktPublishing/Clustering-and-Classification-with-Machine-Learning-in-R
What You Will Learn
Read-in data into the R environment from different sources
Carry out basic data pre-processing and wrangling in R Studio
Implement unsupervised/clustering techniques such as K-means clustering
Implement dimensional reduction techniques (PCA) and feature selection
Implement supervised learning techniques/classification such as Random Forests
Evaluate model performance and learn the best practices for evaluating machine learning model accuracy
Audience
This course is for students interested in getting started with data science applications in the R Studio environment. Students wishing to learn how to implement unsupervised learning on real data. Anyone with prior exposure to R who wants to get started with practical data science.
Approach
Every video is packed with hands-on instructions and clear explanations. Real data has been used to demonstrate how to implement these techniques in real life, on your data.
Key Features
Provides in-depth training in everything you need to know to get started with practical R data science * Jargon-free and suitable for people who have a non-mathematical background * In-depth coverage of the latest unsupervised and supervised techniques 
Github Repo
https://github.com/packtpublishing/clustering-and-classification-with-machine-learning-in-r
About the Author
Minerva Singh
Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.
Course Outline
1. Introduction to the Course

1. Welcome to Clustering & Classification with Machine Learning in R
Introduction to the Course: Welcome to Clustering & Classification with Machine Learning in R
2. Installing R and R Studio
Introduction to the Course: Installing R and R Studio
2. Read in Data from Different Sources in R

1. Read in CSV & Excel Data
Read in Data from Different Sources in R: Read in CSV & Excel Data
2. Read in Unzipped Folder
Read in Data from Different Sources in R: Read in Unzipped Folder
3. Read in Online CSV
Read in Data from Different Sources in R: Read in Online CSV
4. Read in Googlesheets
Read in Data from Different Sources in R: Read in Googlesheets
5. Read in Data from Online HTML Tables-Part 1
Read in Data from Different Sources in R: Read in Data from Online HTML Tables-Part 1
6. Read in Data from Online HTML Tables-Part 2
Read in Data from Different Sources in R: Read in Data from Online HTML Tables-Part 2
7. Read Data from a Database
Read in Data from Different Sources in R: Read Data from a Database
3. Data Pre-processing and Visualization

1. Remove Missing Values
Data Pre-processing and Visualization: Remove Missing Values
2. More Data Cleaning
Data Pre-processing and Visualization: More Data Cleaning
3. Introduction to dplyr for Data Summarizing-Part 1
Data Pre-processing and Visualization: Introduction to dplyr for Data Summarizing-Part 1
4. Introduction to dplyr for Data Summarizing-Part 2
Data Pre-processing and Visualization: Introduction to dplyr for Data Summarizing-Part 2
5. Exploratory Data Analysis (EDA): Basic Visualizations with R
Data Pre-processing and Visualization: Exploratory Data Analysis (EDA): Basic Visualizations with R
6. More Exploratory Data Analysis with xda
Data Pre-processing and Visualization: More Exploratory Data Analysis with xda
7. Data Exploration & Visualization With dplyr & ggplot2
Data Pre-processing and Visualization: Data Exploration & Visualization With dplyr & ggplot2
8. Associations Between Quantitative Variables- Theory
Data Pre-processing and Visualization: Associations Between Quantitative Variables- Theory
9. Testing for Correlation
Data Pre-processing and Visualization: Testing for Correlation
10. Evaluate the Relation Between Nominal Variables
Data Pre-processing and Visualization: Evaluate the Relation Between Nominal Variables
11. Cramer's V for Examining the Strength of Association Between Nominal Variable
Data Pre-processing and Visualization: Cramer's V for Examining the Strength of Association Between Nominal Variable
4. Machine Learning for Data Science

1. How is Machine Learning Different from Statistical Data Analysis?
Machine Learning for Data Science: How is Machine Learning Different from Statistical Data Analysis?
2. What is Machine Learning (ML) About? Some Theoretical Pointers
Machine Learning for Data Science: What is Machine Learning (ML) About? Some Theoretical Pointers
5. Unsupervised Learning in R

1. K-Means Clustering
Unsupervised Learning in R: K-Means Clustering
2. Other Ways of Selecting Cluster Numbers
Unsupervised Learning in R: Other Ways of Selecting Cluster Numbers
3. Fuzzy K-Means Clustering
Unsupervised Learning in R: Fuzzy K-Means Clustering
4. Weighted k-means
Unsupervised Learning in R: Weighted k-means
5. Partitioning Around Meloids (PAM)
Unsupervised Learning in R: Partitioning Around Meloids (PAM)
6. Hierarchical Clustering in R
Unsupervised Learning in R: Hierarchical Clustering in R
7. Expectation-Maximization (EM) in R
Unsupervised Learning in R: Expectation-Maximization (EM) in R
8. DBSCAN Clustering in R
Unsupervised Learning in R: DBSCAN Clustering in R
9. Cluster a Mixed Dataset
Unsupervised Learning in R: Cluster a Mixed Dataset
10. Should We Even Do Clustering?
Unsupervised Learning in R: Should We Even Do Clustering?
11. Assess Clustering Performance
Unsupervised Learning in R: Assess Clustering Performance
12. Which Clustering Algorithm to Choose?
Unsupervised Learning in R: Which Clustering Algorithm to Choose?
6. Feature/Dimension Reduction

1. Dimension Reduction-theory
Feature/Dimension Reduction: Dimension Reduction-theory
2. Principal Component Analysis (PCA)
Feature/Dimension Reduction: Principal Component Analysis (PCA)
3. More on PCA
Feature/Dimension Reduction: More on PCA
4. Multidimensional Scaling
Feature/Dimension Reduction: Multidimensional Scaling
5. Singular Value Decomposition (SVD)
Feature/Dimension Reduction: Singular Value Decomposition (SVD)
7. Feature Selection to Select the Most Relevant Predictors

1. Removing Highly Correlated Predictor Variables
Feature Selection to Select the Most Relevant Predictors: Removing Highly Correlated Predictor Variables
2. Variable Selection Using LASSO Regression
Feature Selection to Select the Most Relevant Predictors: Variable Selection Using LASSO Regression
3. Variable Selection with FSelector
Feature Selection to Select the Most Relevant Predictors: Variable Selection with FSelector
4. Boruta Analysis for Feature Selection
Feature Selection to Select the Most Relevant Predictors: Boruta Analysis for Feature Selection
8. Supervised Learning Theory

1. Some Basic Supervised Learning Concepts
Supervised Learning Theory: Some Basic Supervised Learning Concepts
2. Pre-processing for Supervised Learning
Supervised Learning Theory: Pre-processing for Supervised Learning
9. Supervised Learning: Classification

1. What are GLMs?
Supervised Learning: Classification: What are GLMs?
2. Logistic Regression Models as Binary Classifiers
Supervised Learning: Classification: Logistic Regression Models as Binary Classifiers
3. Binary Classifier with PCA
Supervised Learning: Classification: Binary Classifier with PCA
4. Some Pointers on Evaluating Accuracy
Supervised Learning: Classification: Some Pointers on Evaluating Accuracy
5. Obtain Binary Classification Accuracy Metrics
Supervised Learning: Classification: Obtain Binary Classification Accuracy Metrics
6. More on Binary Accuracy Measures
Supervised Learning: Classification: More on Binary Accuracy Measures
7. Linear Discriminant Analysis
Supervised Learning: Classification: Linear Discriminant Analysis
8. Our Multi-class Classification Problem
Supervised Learning: Classification: Our Multi-class Classification Problem
9. Classification Trees
Supervised Learning: Classification: Classification Trees
10. More on Classification Tree Visualization
Supervised Learning: Classification: More on Classification Tree Visualization
11. Classification with Party Package
Supervised Learning: Classification: Classification with Party Package
12. Decision Trees
Supervised Learning: Classification: Decision Trees
13. Random Forest (RF) Classification
Supervised Learning: Classification: Random Forest (RF) Classification
14. Examine Individual Variable Importance for Random Forests
Supervised Learning: Classification: Examine Individual Variable Importance for Random Forests
15. GBM Classification
Supervised Learning: Classification: GBM Classification
16. Support Vector Machines (SVM) for Classification
Supervised Learning: Classification: Support Vector Machines (SVM) for Classification
17. More SVM for Classification
Supervised Learning: Classification: More SVM for Classification
18. Variable Importance in SVM Modelling with rminer
Supervised Learning: Classification: Variable Importance in SVM Modelling with rminer
10. Additional Lectures

1. Fuzzy C-Means Clustering
Additional Lectures: Fuzzy C-Means Clustering

HTML

The underlying patterns in your data hold vital insights; unearth them with cutting-edge clustering and classification techniques in R

Clustering and Classification with Machine Learning in R

Northampton

Course Description:
Disagreements, differences of opinion and conflicting perspectives on key issues inevitably arise in any context where people are working together.
Research has shown that workplace conflicts can become highly destructive. Negative emotions may be stirred up, poisoning team morale, creating stress and destroying relationships.
Conflict may emerge between managers and their staff, between team members or departments.
Conflict may be expressed openly, but it may also be hidden, in the form of irritation, resentment, loss of morale and lack of commitment. Hidden conflict is easy to miss and therefore can be particularly damaging.
Ultimately, this is likely to have an adverse effect on team and company performance, costing time and money.
It is therefore vital to manage conflict constructively.
As an team member and leader, your ability to deal with and resolve conflicts defines your success in the longer term.
Our one day workshop in Conflict Management and Communication Skills immerses you in the most advanced conflict management tools, strategies and practices applicable today. You will gain hands on practice on proven frameworks, go through simulations and exercises that will train you to be highly effective professional and leader, starting day one.
Course Topics:
1) Science behind workplace conflicts
2) Understanding Human Behaviour
3) Different Personality Types
4) Conflict Management Styles
5) Conflict Management Strategies
6) Workplace Conflicts
7) Conflict Resolution Agreements
8) Working with difficult people
9) Relationship and reputation management
Learning Objectives:
Getting a handle on and gaining insights into your conflict management style through self-assessments (TKI®).
Role playing to practice techniques and new skills in a safe environment.
Proven best practices for approaching conflict management.
Practices for resolving conflict as a third party mediator.
Scientifically validated frameworks on effective communication in stressful situations.
Transferring your learning back to your work environment using job aids, templates and other resources.
How You Will Benefit:
Build trust and credibility with colleagues and team members
Leverage potential conflict situations as opportunities for critical conversations that enhance work relationships.
Gain confidence in holding difficult conversations calmly and assertively.
Manage difficult situations proactively.
Increase your effectiveness in managing conflict.
See growth in your overall performance
Certification:
Once after the training we will provide you the course completion certificate.

Mangates

Catering to the demands of busy professionals, our virtual training programs are as effective as face-to-face learning.

For more queries, reach out to us: info@mangates.com

Conflict Management 1 Day Virtual Live Training in Cambridge

Standard Fee

Early Bird Fee

York

<p data-key="1"><span data-key="2"><strong data-slate-leaf="true">Course Description:</strong></span></p>
<p>Communication Skills are the most highly valued skills in today&rsquo;s business environment. Successful professionals who add value to their companies communicate clearly, accurately and effectively. Poor communication skills, on the other hand, restrict even the most talented professionals from getting ahead in the business world.</p>
<p>Communication Skills intensive is a cutting edge training program designed to help today&rsquo;s business professionals take their communication skills and effectiveness to the next level. It immerses you into the most advanced and innovative communication techniques.</p>
<p>You will dive deep into all forms of verbal, non-verbal and written communication, and come out with a developed sense of personal communication style that will help you to connect with, communicate to, and inspire people around you. The ability to communicate information accurately, clearly and as intended, is a vital life skill and something that should not be overlooked. It&rsquo;s never too late to work on your communication skills and by doing so improve your quality of life.</p>
<p><strong>Target Audience:</strong></p>
<p>There is no Eligibility Criteria for this training, anyone can attend this training</p>
<p><strong>Learning Objectives:</strong></p>
<ul>
<li>Script yourself with clear, compelling and well-developed messages that reflect your thinking .</li>
<li>Speak with vision and a logical structure that drives home your points.</li>
<li>Answer questions confidently.</li>
<li>Develop professional relationships and networks.</li>
<li>Communicate with empathy and compassion .</li>
<li>Inspire people by appealing to their emotions.</li>
<li>Move from an informational to an inspirational and action oriented style when creating and delivering presentations.</li>
<li>Integrate effective slides into your presentations.</li>
<li>Become a more powerful leader and communicator by applying effective strategic planning and writing tactics for enhanced writing speed and fluency.</li>
</ul>
<p><strong>Prerequisites:</strong></p>
<p>There are no prerequisites for this course.</p>
<p><strong>Course Materials:</strong></p>
<p>Students will receive a course manual with presentation slides and reference materials.</p>
<p><strong>Examination:</strong></p>
<p>There is no exam.</p>
<p><strong>Technical Requirements:</strong></p>
<p>For eBooks:</p>
<p>Internet for downloading the eBook</p>
<p>Laptop, tablet, Smartphone, eReader (No Kindle)</p>
<p>Adobe DRM supported software (e.g. Digital Editions, Bluefire Reader)</p>
<p>eBook download and activation instructions</p>
<p><strong>Agenda:</strong></p>
<ul>
<li>The Science of Effective Human Communication</li>
<li>Frames of Business and Communication</li>
<li>Principles and Strategies for Effective Business Conversations</li>
<li>Art of Giving and Receiving Feedback</li>
<li>How to Listen Effectively and Accurately</li>
<li>Science of Body Language</li>
<li>How to look confident and charismatic</li>
<li>Business Presentation Skills and Strategies</li>
<li>Powerpoint Best Practices</li>
<li>Principles and Techniques for Effective Written Communication</li>
<li>How to write clear, concise and fast at the same time</li>
</ul>

Course Description:
Communication Skills are the most highly valued skills in today’s business environment. Successful professionals who add value to their companies communicate clearly, accurately and effectively. Poor communication skills, on the other hand, restrict even the most talented professionals from getting ahead in the business world.
Communication Skills intensive is a cutting edge training program designed to help today’s business professionals take their communication skills and effectiveness to the next level. It immerses you into the most advanced and innovative communication techniques.
You will dive deep into all forms of verbal, non-verbal and written communication, and come out with a developed sense of personal communication style that will help you to connect with, communicate to, and inspire people around you. The ability to communicate information accurately, clearly and as intended, is a vital life skill and something that should not be overlooked. It’s never too late to work on your communication skills and by doing so improve your quality of life.
Target Audience:
There is no Eligibility Criteria for this training, anyone can attend this training
Learning Objectives:
Script yourself with clear, compelling and well-developed messages that reflect your thinking .
Speak with vision and a logical structure that drives home your points.
Answer questions confidently.
Develop professional relationships and networks.
Communicate with empathy and compassion .
Inspire people by appealing to their emotions.
Move from an informational to an inspirational and action oriented style when creating and delivering presentations.
Integrate effective slides into your presentations.
Become a more powerful leader and communicator by applying effective strategic planning and writing tactics for enhanced writing speed and fluency.
Prerequisites:
There are no prerequisites for this course.
Course Materials:
Students will receive a course manual with presentation slides and reference materials.
Examination:
There is no exam.
Technical Requirements:
For eBooks:
Internet for downloading the eBook
Laptop, tablet, Smartphone, eReader (No Kindle)
Adobe DRM supported software (e.g. Digital Editions, Bluefire Reader)
eBook download and activation instructions
Agenda:
The Science of Effective Human Communication
Frames of Business and Communication
Principles and Strategies for Effective Business Conversations
Art of Giving and Receiving Feedback
How to Listen Effectively and Accurately
Science of Body Language
How to look confident and charismatic
Business Presentation Skills and Strategies
Powerpoint Best Practices
Principles and Techniques for Effective Written Communication
How to write clear, concise and fast at the same time

Communication Skills

Communication Skills 1 Day Virtual Live Training in Cambridge

<p>Benefit your career progression while saving a massive amount of your wallet by enrolling in our Ultimate ATHE Level 3 Diploma In Law qualification bundle of Govt regulated and CPD accredited courses!</p><p>What's included with the Level 3 Law Diploma &amp; Contract Law?</p><ul><li>Ofqual Regulated ATHE Level 3 Diploma In Law</li><li>Certificate on ATHE Level 3 Diploma In Law</li><li>Certificate on Contracts Law UK</li><li>1-2-1 tutor support</li><li>24/7 access to Course library</li><li>High quality study modules</li><li>Dedicated customer support</li><li>Assessment guidance</li><li>Assessment</li></ul><p>This super saver ultimate ATHE qualification bundle will add significant value to your resume while creating numerous possibilities for your career advancement.</p><p>Register to discover the abilities and knowledge required to succeed in the field of Law according to the standards established by OFQUAL and stand out to others. Do not rely on shoddy training or a mediocre education. Focus on excellence, and whenever and wherever you need us, we'll support you in achieving your full potential.</p><p>Ensure your degree is acknowledged internationally by joining us today!</p><p><strong>Kingston Open College is the affiliate partner of One Education. Under the affiliate partnership/program this Qualification will be delivered and assessed by One Education.</strong></p><p><strong>***Curriculum Breakdown of ATHE Level 3 Diploma In Law</strong><strong>***</strong></p><p><strong>Mandatory Units</strong></p><ul><li><strong>Unit 01: </strong>The English Legal System</li><li><strong>Unit 02:</strong> Contract Law</li><li><strong>Unit 03:</strong> Legal Terminology and Communication</li><li><strong>Unit 04:</strong> Academic and Research Skills for Law</li></ul><p><strong>***Curriculum Breakdown of Contracts Law UK</strong><strong>***</strong></p><ul><li><strong>Module 01:</strong> Introduction to UK Laws</li><li><strong>Module 02:</strong> Ministry of Justice</li><li><strong>Module 03:</strong> Agreements and Contractual Intention</li><li><strong>Module 04:</strong> Considerations and Capacities of Contact Laws</li><li><strong>Module 05:</strong> Terms within a Contract</li><li><strong>Module 06:</strong> Misinterpretations and Mistakes</li><li><strong>Module 07:</strong> Consumer Protection</li><li><strong>Module 08:</strong> Privity of Contract</li><li><strong>Module 09:</strong> Insurance Contract Laws</li><li><strong>Module 10:</strong> Contracts for Employees</li><li><strong>Module 11:</strong> Considerations in International Trade Contracts</li><li><strong>Module 12:</strong> Laws and Regulations for International Trade</li><li><strong>Module 13:</strong> Remedies for Any Contract Breach</li></ul><p><strong>Total Qualification Time</strong></p><p>Total Qualification contains the Guided Learning Hours (GLH) and an estimated number of hours that a learner is likely to spend in preparation, study, or any other learning including assessment, taking place as directed by, but not under the supervision of a lecturer, supervisor or tutor.</p><p>The expected total length of time that a learner will typically take to achieve and demonstrate the level of attainment necessary for the award of the qualification is 650 hours, where one credit corresponds to 10 hours of learning.</p><p><strong>So the TQT value is </strong><strong>600</strong><strong>.</strong></p><p><strong>Guided Learning Hours</strong></p><p>These hours comprise all contact time, guidance or supervision of a learner by a lecturer, supervisor, tutor, trainer or other appropriate providers of education or training.</p><p><strong>GLH for this qualification is </strong><strong>360</strong><strong>.</strong></p><p><strong>Assessment:</strong></p><p>For the ATHE Level 3 Diploma In Law, learners will have to prepare a written assignment that will be initially assessed by a qualified assessor and further assessed by an IQA to ensure that all the learning outcomes of the qualification are properly accomplished by the learner.</p><p><strong>Certification:</strong></p><p><strong>Ofqual Regulated Certificate:</strong> Learners will be issued with ATHE awarded certificate upon successful completion of the qualification assessment. It will not require any further cost at all.</p><p><strong>CPD Accredited Certification:</strong> For the Contracts Law UK course certificate. Learners don't have to pay any additional payment.</p><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This course is designed for individuals who are interested in studying and gaining a comprehensive understanding of law, particularly contract law, in the United Kingdom. The course is suitable for various groups, including:</p><ul><li>Aspiring Law Students</li><li>Legal Professionals</li><li>Business Professionals</li><li>Individuals Seeking Legal Knowledge</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This qualification is designed for learners aged 16 and above and have recently been in education or training the entry profile is likely to include one of the following:</p><ul><li>5 or more GCSEs at grades C and above</li><li>other related level 2 subjects</li><li>other equivalent international qualifications</li></ul><p>For those whom English is not their first language, we recommend the following standards of proficiency in English language skills or an approved equivalent for this qualification:</p><ul><li><ul><li>IELTS 5.5</li><li>Common European Framework of Reference (CEFR) B2</li><li>Cambridge English Advanced (CAE) 162 or above</li><li>Pearson Test of English (PTE) Academic 42-49</li></ul></li></ul>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li><strong>Law Tutor. </strong>£50,000 per annum</li><li><strong>Legal PA Personal Assistant:</strong> £30,000 per annum</li><li><strong>Solicitor:</strong> £65,000 - £80,000 per annum</li><li><strong>Paralegal</strong>: £21,000 - £30,000 per annum</li><li><strong>Costs Advocate</strong>: £50,000 per annum</li></ul>
                        </div>

Benefit your career progression while saving a massive amount of your wallet by enrolling in our Ultimate ATHE Level 3 Diploma In Law qualification bundle of Govt regulated and CPD accredited courses!
What's included with the Level 3 Law Diploma & Contract Law?
Ofqual Regulated ATHE Level 3 Diploma In Law
Certificate on ATHE Level 3 Diploma In Law
Certificate on Contracts Law UK
1-2-1 tutor support
24/7 access to Course library
High quality study modules
Dedicated customer support
Assessment guidance
Assessment
This super saver ultimate ATHE qualification bundle will add significant value to your resume while creating numerous possibilities for your career advancement.
Register to discover the abilities and knowledge required to succeed in the field of Law according to the standards established by OFQUAL and stand out to others. Do not rely on shoddy training or a mediocre education. Focus on excellence, and whenever and wherever you need us, we'll support you in achieving your full potential.
Ensure your degree is acknowledged internationally by joining us today!
Kingston Open College is the affiliate partner of One Education. Under the affiliate partnership/program this Qualification will be delivered and assessed by One Education.
***Curriculum Breakdown of ATHE Level 3 Diploma In Law***
Mandatory Units
Unit 01: The English Legal System
Unit 02: Contract Law
Unit 03: Legal Terminology and Communication
Unit 04: Academic and Research Skills for Law
***Curriculum Breakdown of Contracts Law UK***
Module 01: Introduction to UK Laws
Module 02: Ministry of Justice
Module 03: Agreements and Contractual Intention
Module 04: Considerations and Capacities of Contact Laws
Module 05: Terms within a Contract
Module 06: Misinterpretations and Mistakes
Module 07: Consumer Protection
Module 08: Privity of Contract
Module 09: Insurance Contract Laws
Module 10: Contracts for Employees
Module 11: Considerations in International Trade Contracts
Module 12: Laws and Regulations for International Trade
Module 13: Remedies for Any Contract Breach
Total Qualification Time
Total Qualification contains the Guided Learning Hours (GLH) and an estimated number of hours that a learner is likely to spend in preparation, study, or any other learning including assessment, taking place as directed by, but not under the supervision of a lecturer, supervisor or tutor.
The expected total length of time that a learner will typically take to achieve and demonstrate the level of attainment necessary for the award of the qualification is 650 hours, where one credit corresponds to 10 hours of learning.
So the TQT value is 600.
Guided Learning Hours
These hours comprise all contact time, guidance or supervision of a learner by a lecturer, supervisor, tutor, trainer or other appropriate providers of education or training.
GLH for this qualification is 360.
Assessment:
For the ATHE Level 3 Diploma In Law, learners will have to prepare a written assignment that will be initially assessed by a qualified assessor and further assessed by an IQA to ensure that all the learning outcomes of the qualification are properly accomplished by the learner.
Certification:
Ofqual Regulated Certificate: Learners will be issued with ATHE awarded certificate upon successful completion of the qualification assessment. It will not require any further cost at all.
CPD Accredited Certification: For the Contracts Law UK course certificate. Learners don't have to pay any additional payment.
 Who is this course for? 
This course is designed for individuals who are interested in studying and gaining a comprehensive understanding of law, particularly contract law, in the United Kingdom. The course is suitable for various groups, including:
Aspiring Law Students
Legal Professionals
Business Professionals
Individuals Seeking Legal Knowledge
 Requirements 
This qualification is designed for learners aged 16 and above and have recently been in education or training the entry profile is likely to include one of the following:
5 or more GCSEs at grades C and above
other related level 2 subjects
other equivalent international qualifications
For those whom English is not their first language, we recommend the following standards of proficiency in English language skills or an approved equivalent for this qualification:
IELTS 5.5Common European Framework of Reference (CEFR) B2Cambridge English Advanced (CAE) 162 or abovePearson Test of English (PTE) Academic 42-49
 Career path 
Law Tutor. £50,000 per annum
Legal PA Personal Assistant: £30,000 per annum
Solicitor: £65,000 - £80,000 per annum
Paralegal: £21,000 - £30,000 per annum
Costs Advocate: £50,000 per annum

Kingston Open College

LLB (Bachelor of Laws)

Certificate in Further Education & Training (Cert Ed)

Legal Practice Course (LPC)

FA Level 1

Central Law Training (CLT)

Graduate Diploma in Law (GDL)

Premium Bundle of all Time | Ofqual Regulation + ATHE Awards + CPD Accreditation | Assessment & Tutor Support Included

Level 3 Law Diploma & Contract Law

<strong>Gain proficiency in the mastery of Geographic Information Systems (GIS) via ArcGIS Desktop</strong>
        <p>This course teaches you the most important aspects of spatial data analysis using ArcGIS. It is highly beneficial for both those wanting to learn spatial data analysis and/or gain familiarity with the ArcGIS ecosystem

First, we'll start some basic GIS tasks like 'Zooming'. Then, we'll move into more complex processing tasks like 'Geo-Statistics'. We'll also deal with some theoretical concepts related to Spatial Data Analysis, and then we'll focus on implementing some of the most common GIS techniques (all the way showing you how to execute these tasks in ArcGIS Desktop).

The stuff you'll learn from this course will be extremely useful in terms of you being able to implement it on future Spatial Data projects you'll be working on. The course is a hands-on training with real data. It's a step by step course covering both the theory and application of Spatial Data Analysis. This is one of the most comprehensive courses on this topic.  

All the code and supporting files for this course are available at -
https://github.com/PacktPublishing/ArcGIS-Desktop-For-Spatial-Analysis-Go-From-Basic-To-Pro</p>
        <h2>What You Will Learn</h2><p>You will have a thorough knowledge of the ArcGIS Interface and Functionality<br>You will learn about the different toolboxes in ArcGIS and what they can do<br>You can carry out practical spatial data analysis tasks, geoprocessing and mapping using ArcGIS Desktop<br>You learn about advanced topics such as geostatistics and carry them out on actual data<br>You visualize and map spatial data</p>
        <h2>Audience</h2><p>The target audience is the people looking to get started in the field of GIS Analysis use ArcGIS Desktop in academic or professional settings and students should have access to ArcGIS Desktop. You should have prior knowledge of basic spatial data related concepts such as the different data types and coordinate systems.</p>
        <h2>Approach</h2><p>The approach is full of hands-on instructions via video-lectures, interesting and illustrative examples, clear explanations. Each video lecture will teach you a new concept that you can apply to your own data.</p>
        <h2>Key Features</h2><p>The course will teach you to implement some of the most important spatial data analysis techniques in ArcGIS Desktop * You learn to work with real spatial data * Carry our practical map making to display the results of spatial analysis * Learn about advanced topics such as geostatistics and carry them out on actual data</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/arcgis-desktop-for-spatial-analysis-go-from-basic-to-pro</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Welcome to Spatial Data Analysis and Visualization</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What is this Course About and Meet the Instructor</p><p style='margin: 0'>Welcome to Spatial Data Analysis and Visualization: What is this Course About and Meet the Instructor</p></td></tr><tr><td style='padding: 15px;'><p>2. Some Spatial Data Analysis Related Concepts</p><p style='margin: 0'>Welcome to Spatial Data Analysis and Visualization: Some Spatial Data Analysis Related Concepts</p></td></tr><tr><td style='padding: 15px;'><p>3. Conclusion to Section 1</p><p style='margin: 0'>Welcome to Spatial Data Analysis and Visualization: Conclusion to Section 1</p></td></tr></tbody></table><br><h4>2. Introduction to ArcGIS Desktop and its Functionality</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What is ArcGIS Desktop?</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: What is ArcGIS Desktop?</p></td></tr><tr><td style='padding: 15px;'><p>2. Accessing and Displaying Spatial Data in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Accessing and Displaying Spatial Data in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>3. Finding and identifying Features and Values in ArcGIS Desktop</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Finding and identifying Features and Values in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>4. Making Selections in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Making Selections in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Zooming and Measuring</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Zooming and Measuring</p></td></tr><tr><td style='padding: 15px;'><p>6. Calculate Shapefile Geometry in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Calculate Shapefile Geometry in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>7. Working With Different Coordinate Systems in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Working With Different Coordinate Systems in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusion to Section 2</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Conclusion to Section 2</p></td></tr></tbody></table><br><h4>3. Working with Raster Data in ArcGIS Desktop</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Displaying Raster Data in ArcGIS</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Displaying Raster Data in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>2. Merge Rasters in ArcGIS</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Merge Rasters in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>3. Band Arithmetic in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Band Arithmetic in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>4. Reclassify a Raster in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Reclassify a Raster in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>5. Resample a Raster in ArcGIS</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Resample a Raster in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Topographic Data Products-Brief Theoretical Introduction</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Topographic Data Products-Brief Theoretical Introduction</p></td></tr><tr><td style='padding: 15px;'><p>7. Topographic Calculations in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Topographic Calculations in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>8. Clip a Raster to the Extent of a Polygon in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Clip a Raster to the Extent of a Polygon in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>9. Zonal Statistics</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Zonal Statistics</p></td></tr><tr><td style='padding: 15px;'><p>10. Extract Raster Values to Points</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Extract Raster Values to Points</p></td></tr><tr><td style='padding: 15px;'><p>11. Geo-referencing a Raster in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Geo-referencing a Raster in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>12. Conclusion to Section 3</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Conclusion to Section 3</p></td></tr></tbody></table><br><h4>4. Working with Vector Data in ArcGIS Desktop</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Exploratory Data Analysis with Shapefile Attributes in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Exploratory Data Analysis with Shapefile Attributes in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>2. Basic Graphing of Shapefile Attributes in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Basic Graphing of Shapefile Attributes in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>3. Spatial Join with Tabular Data</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Spatial Join with Tabular Data</p></td></tr><tr><td style='padding: 15px;'><p>4. Spatial Joins in ArcGIS Based on Spatial Location</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Spatial Joins in ArcGIS Based on Spatial Location</p></td></tr><tr><td style='padding: 15px;'><p>5. Create Choropleth Maps</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Create Choropleth Maps</p></td></tr><tr><td style='padding: 15px;'><p>6. Split Shapefiles Using ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Split Shapefiles Using ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>7. Clip Shapefile in ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Clip Shapefile in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Intersection of Shapefiles in ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Intersection of Shapefiles in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>9. Add Buffer Areas to Shapefiles in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Add Buffer Areas to Shapefiles in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>10. Merge and Append Shapefiles in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Merge and Append Shapefiles in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>11. Dissolve Shapefiles in ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Dissolve Shapefiles in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>12. Conclusion to Section 4</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Conclusion to Section 4</p></td></tr></tbody></table><br><h4>5. More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Euclidean Distance Raster Generation in ArcGIS Desktop</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Euclidean Distance Raster Generation in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>2. Density Analysis in ArcGIS Desktop</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Density Analysis in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>3. Compute Line Density in ArcGIS</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Compute Line Density in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>4. Compute Point Density in ArcGIS</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Compute Point Density in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Kernel Density for Linear and Point Features in ArcGIS</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Kernel Density for Linear and Point Features in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Interpolation of Point Data-Theory</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Interpolation of Point Data-Theory</p></td></tr><tr><td style='padding: 15px;'><p>7. Interpolation of Point Data-Application</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Interpolation of Point Data-Application</p></td></tr><tr><td style='padding: 15px;'><p>8. Mapping Spatial Clusters in ArcGIS Desktop-Theory</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Mapping Spatial Clusters in ArcGIS Desktop-Theory</p></td></tr><tr><td style='padding: 15px;'><p>9. Mapping Spatial Clusters in ArcGIS Desktop-Application</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Mapping Spatial Clusters in ArcGIS Desktop-Application</p></td></tr><tr><td style='padding: 15px;'><p>10. Geographically Weighted Regression in ArcGIS-Theory</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Geographically Weighted Regression in ArcGIS-Theory</p></td></tr><tr><td style='padding: 15px;'><p>11. Geographically Weighted Regression in ArcGIS-Application</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Geographically Weighted Regression in ArcGIS-Application</p></td></tr><tr><td style='padding: 15px;'><p>12. Model Builder for Automating Geoprocessing</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Model Builder for Automating Geoprocessing</p></td></tr><tr><td style='padding: 15px;'><p>13. Conclusion to Section 5</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Conclusion to Section 5</p></td></tr></tbody></table><br><h4>6. Make Simple Maps in ArcGIS</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Examples of ArcGIS Maps</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Examples of ArcGIS Maps</p></td></tr><tr><td style='padding: 15px;'><p>2. Presenting Spatial Data As a Layer File</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Presenting Spatial Data As a Layer File</p></td></tr><tr><td style='padding: 15px;'><p>3. Using Base Maps provided by ArcGIS to Provide Context to Our Map</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Using Base Maps provided by ArcGIS to Provide Context to Our Map</p></td></tr><tr><td style='padding: 15px;'><p>4. Putting Together a Map</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Putting Together a Map</p></td></tr><tr><td style='padding: 15px;'><p>5. Conclusion to Section 6</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Conclusion to Section 6</p></td></tr></tbody></table>

Gain proficiency in the mastery of Geographic Information Systems (GIS) via ArcGIS Desktop
This course teaches you the most important aspects of spatial data analysis using ArcGIS. It is highly beneficial for both those wanting to learn spatial data analysis and/or gain familiarity with the ArcGIS ecosystem First, we'll start some basic GIS tasks like 'Zooming'. Then, we'll move into more complex processing tasks like 'Geo-Statistics'. We'll also deal with some theoretical concepts related to Spatial Data Analysis, and then we'll focus on implementing some of the most common GIS techniques (all the way showing you how to execute these tasks in ArcGIS Desktop). The stuff you'll learn from this course will be extremely useful in terms of you being able to implement it on future Spatial Data projects you'll be working on. The course is a hands-on training with real data. It's a step by step course covering both the theory and application of Spatial Data Analysis. This is one of the most comprehensive courses on this topic. All the code and supporting files for this course are available at -
https://github.com/PacktPublishing/ArcGIS-Desktop-For-Spatial-Analysis-Go-From-Basic-To-Pro
What You Will Learn
You will have a thorough knowledge of the ArcGIS Interface and Functionality
You will learn about the different toolboxes in ArcGIS and what they can do
You can carry out practical spatial data analysis tasks, geoprocessing and mapping using ArcGIS Desktop
You learn about advanced topics such as geostatistics and carry them out on actual data
You visualize and map spatial data
Audience
The target audience is the people looking to get started in the field of GIS Analysis use ArcGIS Desktop in academic or professional settings and students should have access to ArcGIS Desktop. You should have prior knowledge of basic spatial data related concepts such as the different data types and coordinate systems.
Approach
The approach is full of hands-on instructions via video-lectures, interesting and illustrative examples, clear explanations. Each video lecture will teach you a new concept that you can apply to your own data.
Key Features
The course will teach you to implement some of the most important spatial data analysis techniques in ArcGIS Desktop * You learn to work with real spatial data * Carry our practical map making to display the results of spatial analysis * Learn about advanced topics such as geostatistics and carry them out on actual data
Github Repo
https://github.com/packtpublishing/arcgis-desktop-for-spatial-analysis-go-from-basic-to-pro
About the Author
Minerva Singh
Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.
Course Outline
1. Welcome to Spatial Data Analysis and Visualization

1. What is this Course About and Meet the Instructor
Welcome to Spatial Data Analysis and Visualization: What is this Course About and Meet the Instructor
2. Some Spatial Data Analysis Related Concepts
Welcome to Spatial Data Analysis and Visualization: Some Spatial Data Analysis Related Concepts
3. Conclusion to Section 1
Welcome to Spatial Data Analysis and Visualization: Conclusion to Section 1
2. Introduction to ArcGIS Desktop and its Functionality

1. What is ArcGIS Desktop?
Introduction to ArcGIS Desktop and its Functionality: What is ArcGIS Desktop?
2. Accessing and Displaying Spatial Data in ArcGIS
Introduction to ArcGIS Desktop and its Functionality: Accessing and Displaying Spatial Data in ArcGIS
3. Finding and identifying Features and Values in ArcGIS Desktop
Introduction to ArcGIS Desktop and its Functionality: Finding and identifying Features and Values in ArcGIS Desktop
4. Making Selections in ArcGIS
Introduction to ArcGIS Desktop and its Functionality: Making Selections in ArcGIS
5. Zooming and Measuring
Introduction to ArcGIS Desktop and its Functionality: Zooming and Measuring
6. Calculate Shapefile Geometry in ArcGIS
Introduction to ArcGIS Desktop and its Functionality: Calculate Shapefile Geometry in ArcGIS
7. Working With Different Coordinate Systems in ArcGIS
Introduction to ArcGIS Desktop and its Functionality: Working With Different Coordinate Systems in ArcGIS
8. Conclusion to Section 2
Introduction to ArcGIS Desktop and its Functionality: Conclusion to Section 2
3. Working with Raster Data in ArcGIS Desktop

1. Displaying Raster Data in ArcGIS
Working with Raster Data in ArcGIS Desktop: Displaying Raster Data in ArcGIS
2. Merge Rasters in ArcGIS
Working with Raster Data in ArcGIS Desktop: Merge Rasters in ArcGIS
3. Band Arithmetic in ArcGIS Desktop
Working with Raster Data in ArcGIS Desktop: Band Arithmetic in ArcGIS Desktop
4. Reclassify a Raster in ArcGIS Desktop
Working with Raster Data in ArcGIS Desktop: Reclassify a Raster in ArcGIS Desktop
5. Resample a Raster in ArcGIS
Working with Raster Data in ArcGIS Desktop: Resample a Raster in ArcGIS
6. Topographic Data Products-Brief Theoretical Introduction
Working with Raster Data in ArcGIS Desktop: Topographic Data Products-Brief Theoretical Introduction
7. Topographic Calculations in ArcGIS Desktop
Working with Raster Data in ArcGIS Desktop: Topographic Calculations in ArcGIS Desktop
8. Clip a Raster to the Extent of a Polygon in ArcGIS Desktop
Working with Raster Data in ArcGIS Desktop: Clip a Raster to the Extent of a Polygon in ArcGIS Desktop
9. Zonal Statistics
Working with Raster Data in ArcGIS Desktop: Zonal Statistics
10. Extract Raster Values to Points
Working with Raster Data in ArcGIS Desktop: Extract Raster Values to Points
11. Geo-referencing a Raster in ArcGIS Desktop
Working with Raster Data in ArcGIS Desktop: Geo-referencing a Raster in ArcGIS Desktop
12. Conclusion to Section 3
Working with Raster Data in ArcGIS Desktop: Conclusion to Section 3
4. Working with Vector Data in ArcGIS Desktop

1. Exploratory Data Analysis with Shapefile Attributes in ArcGIS Desktop
Working with Vector Data in ArcGIS Desktop: Exploratory Data Analysis with Shapefile Attributes in ArcGIS Desktop
2. Basic Graphing of Shapefile Attributes in ArcGIS Desktop
Working with Vector Data in ArcGIS Desktop: Basic Graphing of Shapefile Attributes in ArcGIS Desktop
3. Spatial Join with Tabular Data
Working with Vector Data in ArcGIS Desktop: Spatial Join with Tabular Data
4. Spatial Joins in ArcGIS Based on Spatial Location
Working with Vector Data in ArcGIS Desktop: Spatial Joins in ArcGIS Based on Spatial Location
5. Create Choropleth Maps
Working with Vector Data in ArcGIS Desktop: Create Choropleth Maps
6. Split Shapefiles Using ArcGIS
Working with Vector Data in ArcGIS Desktop: Split Shapefiles Using ArcGIS
7. Clip Shapefile in ArcGIS
Working with Vector Data in ArcGIS Desktop: Clip Shapefile in ArcGIS
8. Intersection of Shapefiles in ArcGIS
Working with Vector Data in ArcGIS Desktop: Intersection of Shapefiles in ArcGIS
9. Add Buffer Areas to Shapefiles in ArcGIS Desktop
Working with Vector Data in ArcGIS Desktop: Add Buffer Areas to Shapefiles in ArcGIS Desktop
10. Merge and Append Shapefiles in ArcGIS Desktop
Working with Vector Data in ArcGIS Desktop: Merge and Append Shapefiles in ArcGIS Desktop
11. Dissolve Shapefiles in ArcGIS
Working with Vector Data in ArcGIS Desktop: Dissolve Shapefiles in ArcGIS
12. Conclusion to Section 4
Working with Vector Data in ArcGIS Desktop: Conclusion to Section 4
5. More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics

1. Euclidean Distance Raster Generation in ArcGIS Desktop
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Euclidean Distance Raster Generation in ArcGIS Desktop
2. Density Analysis in ArcGIS Desktop
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Density Analysis in ArcGIS Desktop
3. Compute Line Density in ArcGIS
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Compute Line Density in ArcGIS
4. Compute Point Density in ArcGIS
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Compute Point Density in ArcGIS
5. Kernel Density for Linear and Point Features in ArcGIS
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Kernel Density for Linear and Point Features in ArcGIS
6. Interpolation of Point Data-Theory
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Interpolation of Point Data-Theory
7. Interpolation of Point Data-Application
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Interpolation of Point Data-Application
8. Mapping Spatial Clusters in ArcGIS Desktop-Theory
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Mapping Spatial Clusters in ArcGIS Desktop-Theory
9. Mapping Spatial Clusters in ArcGIS Desktop-Application
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Mapping Spatial Clusters in ArcGIS Desktop-Application
10. Geographically Weighted Regression in ArcGIS-Theory
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Geographically Weighted Regression in ArcGIS-Theory
11. Geographically Weighted Regression in ArcGIS-Application
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Geographically Weighted Regression in ArcGIS-Application
12. Model Builder for Automating Geoprocessing
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Model Builder for Automating Geoprocessing
13. Conclusion to Section 5
More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Conclusion to Section 5
6. Make Simple Maps in ArcGIS

1. Examples of ArcGIS Maps
Make Simple Maps in ArcGIS: Examples of ArcGIS Maps
2. Presenting Spatial Data As a Layer File
Make Simple Maps in ArcGIS: Presenting Spatial Data As a Layer File
3. Using Base Maps provided by ArcGIS to Provide Context to Our Map
Make Simple Maps in ArcGIS: Using Base Maps provided by ArcGIS to Provide Context to Our Map
4. Putting Together a Map
Make Simple Maps in ArcGIS: Putting Together a Map
5. Conclusion to Section 6
Make Simple Maps in ArcGIS: Conclusion to Section 6

Gain proficiency in the mastery of Geographic Information Systems (GIS) via ArcGIS Desktop

ArcGIS Desktop for Spatial Analysis: Go from Basic to Pro

<p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">A standalone 10-week course - 2 hours per week online with daytime and evening options - that will introduce you to the materials, tools, and techniques used in quilling and to Craft4Smiles C.I.C and our tutors. &nbsp; At the end of each session you will have a lovely quilled item to show family and friends or to display on your shelf! You will be told about the other courses we offer so that you can make an informed choice about further learning. Participants in this course often move on to our Introduction to Paper Craft and Mixed Media Course that will introduce you to the basic materials, tools, equipment and techniques used. Experience has shown us that participants for whom English is not their first language, have found that quilling has helped them improve their understanding and spoken English as there is a lot of repetition of basic terms including numbers, colours and directions. Working with someon for whom English is their first language is also helpful.&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Programme</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Week 1: Basic Shapes (1)</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Week 2: Basic Shapes and Use of a Quilling Comb (2)&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Week 3: Flower and Butterfly: Picture 8&rdquo; x 10&rdquo;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Week 4: Making a Shape to Hold Quilled Pieces: Capital Letter</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Week 6: Basket of Flowers</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Week 7: Cherry Blossom Box</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Week 8: 2 x 5&rdquo; x 7&rdquo; Pictures: Duck and Boat</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Week 11: Pot of Lavender (1)&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Week 10: Pot of Lavender (2)</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will receive all the materials and items of equipment needed to complete the course. These are yours to keep:&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Materials and Equipment</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&nbsp;</strong>Quilling Kit:&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Quilling Paper Strips: 39 mm: a variety of colours</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Quilling Paper Strips: 39 mm: white</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Quilling Board</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Needlemaker&#39;s Wheel of Pins</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Quilling Formers x 2&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Quilling Comb</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">1 Pair Tweezers</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Pokey Tool</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Quilling Tool: Short</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Quilling Tool: Long</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Scissors</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Glue Applicator</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Book Binders&rsquo; Glue 30 ml</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Black and white 300 gsm card for box and picture</p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(65, 65, 65); font-size: 14px; box-sizing: border-box;" fr-original-style="color: rgb(65, 65, 65); font-size: 14px;">Craft4Smiles C.I.C. is crafting community that&nbsp;</span><span style="color: rgb(0, 0, 0); font-size: 14px; box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0); font-size: 14px;">provides accessible high quality creative papercraft and mixed media online programmes for adults. Our courses are social and interactive whether delivered online or in-person. Our aim is to introduce and build crafting skills and the basic skills needed for success in the workplace and at home, including self-confidence, problem solving, communicating in a group, basic maths and English. We teach over 45 different paper craft and mixed media techniques. Each course is carefully constructed to help you develop your crafting skills and knowledge. &nbsp;</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); font-size: 14px; box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0); font-size: 14px;">Crafting and our courses are mindful, taking us away from the day-to-day. Participants have consistently reported improvements in their wellbeing. &nbsp;Anyone who wants to learn new skills can join our programmes. &nbsp;No previous experience of papercrafting or mixed media work is needed. We have delivered courses successfully in Cambridgeshire for 6 1/2 years and have worked with 280 Cambridges residents during this time. 86% of participants state that what we offer has helped to improve their wellbeing. 75% state that it has made a positive difference to their daily lives. &nbsp;</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); font-size: 14px; box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0); font-size: 14px;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(0, 0, 0);">Please note that the Cademy calenda/description states that this course is over 13 weeks. This is because the 10 weeks of the course are delivered over 13 weeks, during 3 of which, Craft4Smiles is closed for holidays!&nbsp;</span><br fr-original-style="" style="box-sizing: border-box;"></span></p>

A standalone 10-week course - 2 hours per week online with daytime and evening options - that will introduce you to the materials, tools, and techniques used in quilling and to Craft4Smiles C.I.C and our tutors. At the end of each session you will have a lovely quilled item to show family and friends or to display on your shelf! You will be told about the other courses we offer so that you can make an informed choice about further learning. Participants in this course often move on to our Introduction to Paper Craft and Mixed Media Course that will introduce you to the basic materials, tools, equipment and techniques used. Experience has shown us that participants for whom English is not their first language, have found that quilling has helped them improve their understanding and spoken English as there is a lot of repetition of basic terms including numbers, colours and directions. Working with someon for whom English is their first language is also helpful. 
Programme
Week 1: Basic Shapes (1)
Week 2: Basic Shapes and Use of a Quilling Comb (2) 
Week 3: Flower and Butterfly: Picture 8” x 10”
Week 4: Making a Shape to Hold Quilled Pieces: Capital Letter
Week 6: Basket of Flowers
Week 7: Cherry Blossom Box
Week 8: 2 x 5” x 7” Pictures: Duck and Boat
Week 11: Pot of Lavender (1) 
Week 10: Pot of Lavender (2)
You will receive all the materials and items of equipment needed to complete the course. These are yours to keep: 
Materials and Equipment
 Quilling Kit: 
Quilling Paper Strips: 39 mm: a variety of colours
Quilling Paper Strips: 39 mm: white
Quilling Board
Needlemaker's Wheel of Pins
Quilling Formers x 2 
Quilling Comb
1 Pair Tweezers
Pokey Tool
Quilling Tool: Short
Quilling Tool: Long
Scissors
Glue Applicator
Book Binders’ Glue 30 ml
Black and white 300 gsm card for box and picture
Craft4Smiles C.I.C. is crafting community that provides accessible high quality creative papercraft and mixed media online programmes for adults. Our courses are social and interactive whether delivered online or in-person. Our aim is to introduce and build crafting skills and the basic skills needed for success in the workplace and at home, including self-confidence, problem solving, communicating in a group, basic maths and English. We teach over 45 different paper craft and mixed media techniques. Each course is carefully constructed to help you develop your crafting skills and knowledge. 
Crafting and our courses are mindful, taking us away from the day-to-day. Participants have consistently reported improvements in their wellbeing. Anyone who wants to learn new skills can join our programmes. No previous experience of papercrafting or mixed media work is needed. We have delivered courses successfully in Cambridgeshire for 6 1/2 years and have worked with 280 Cambridges residents during this time. 86% of participants state that what we offer has helped to improve their wellbeing. 75% state that it has made a positive difference to their daily lives. 
Please note that the Cademy calenda/description states that this course is over 13 weeks. This is because the 10 weeks of the course are delivered over 13 weeks, during 3 of which, Craft4Smiles is closed for holidays! 


Craft4Smiles C.I.C. 

A standalone 10-week quilling course - 2 hours per week online with daytime and evening options - that will introduce you to the materials, tools, and techniques used in quilling and to Craft4Smiles C.I.C and our tutors.   At the end of each session you will have a lovely quilled item to show family and friends or to display on your shelf!  All materials and equipment needed will be supplied and are yours to keep. This course is helpful for those for whom English is not their native tongue as there is a lot of repetition of basic terms including numbers, colours and directions.  

Quilling

Craft4Smiles Cademy Launch

Quilling - Monday 19.00 - 21.00 or Tuesday 19.00 - 21.00


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					<div><p>Gain the skills and credentials to kick start a successful career and learn from the experts with this step-by-step training course. This GCSE English has been specially designed to help learners gain a good command of GCSE English, providing them with a solid foundation of knowledge to become a qualified professional.</p><p>Through this GCSE English, you will gain both practical and theoretical understanding of GCSE English that will increase your employability in this field, help you stand out from the competition and boost your earning potential in no time.</p><p>Not only that, but this training includes up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the industry. This qualification is fully accredited, broken down into several manageable modules, ideal for aspiring professionals. </p></div>
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										<span>Study at your convenient time and from wherever you want</span>
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										<span>You will receive a completion certificate upon completing the course.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Internationally recognized Accredited Qualification will boost up your resume.</span>
									</li>
								<li>
											<span>
													</span>
										<span>You will learn the researched and proven approach adopted by successful people to transform their careers.</span>
									</li>
								<li>
											<span>
													</span>
										<span>You will be able to incorporate various techniques successfully and understand your customers better.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Requirements</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>No formal qualifications required, anyone from any academic background can take this course.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Access to a computer or digital device with internet connectivity.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section><div>
                            <div>
                                <h2>Course Curriculum</h2>
                            </div>
                            			<div>
				

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4"><strong>Module 01: Introduction to GCSE English</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Introduction to GCSE English</td><td><span>🕐 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 02: Edexcel English Section A Part 01</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Edexcel English Section A Part 01</td><td><span>🕐 00:17:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 03: Edexcel English Section A Part 02</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Edexcel English Section A Part 02</td><td><span>🕐 00:17:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 04: Edexcel English Section B</strong></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Edexcel English Section B</td><td><span>🕐 00:20:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 05: Edexcel English Section C</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Edexcel English Section C</td><td><span>🕐 00:18:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 06: Cambridge English Exercise 1-4</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Cambridge English Exercise 1-4</td><td><span>🕐 00:22:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 07: Cambridge English Exercise 5</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Cambridge English Exercise 5</td><td><span>🕐 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 08: Cambridge English Exercise 6</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Cambridge English Exercise 6</td><td><span>🕐 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 09: Basics of Grammar Part 01</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Basics of Grammar Part 01</td><td><span>🕐 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 10: Basics of Grammar Part 02</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Basics of Grammar Part 02</td><td><span>🕐 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 11: The Basics of Sentences</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>The Basics of Sentences</td><td><span>🕐 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 12: Structure of Sentences</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Structure of Sentences</td><td><span>🕐 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 13: English Language Reading Part 01</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>English Language Reading Part 01</td><td><span>🕐 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 14: English Language Reading Part 02</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>English Language Reading Part 02</td><td><span>🕐 00:14:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 15: English Academic Writing Part 01</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>English Academic Writing Part 01</td><td><span>🕐 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 16: English Academic Writing Part 02</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>English Academic Writing Part 02</td><td><span>🕐 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 17: Punctuation and Capitalisation in Writing</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Punctuation and Capitalization in Writing</td><td><span>🕐 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 18: Most Common Mistakes and How to Avoid Them</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Most Common Mistakes and How to Avoid Them</td><td><span>🕐 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 19: Cambridge English Listening</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Cambridge English Listening</td><td><span>🕐 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 20: Cambridge English Speaking</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Cambridge English Speaking</td><td><span>🕐 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Assignment</strong></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assignment - GCSE English</td><td><span>🕐 05:01:00</span></td>
				</tr>
				</tbody></table></div>

			</div>
		                        </div>

Gain the skills and credentials to kick start a successful career and learn from the experts with this step-by-step training course. This GCSE English has been specially designed to help learners gain a good command of GCSE English, providing them with a solid foundation of knowledge to become a qualified professional.
Through this GCSE English, you will gain both practical and theoretical understanding of GCSE English that will increase your employability in this field, help you stand out from the competition and boost your earning potential in no time.
Not only that, but this training includes up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the industry. This qualification is fully accredited, broken down into several manageable modules, ideal for aspiring professionals. 
 Learning outcome
Familiar yourself with the recent development and updates of the relevant industry
Know how to use your theoretical knowledge to adapt in any working environment
Get help from our expert tutors anytime you need
Access to course contents that are designed and prepared by industry professionals
Study at your convenient time and from wherever you want
 Why should I take this course?
Affordable premium-quality E-learning content, you can learn at your own pace.
You will receive a completion certificate upon completing the course.
Internationally recognized Accredited Qualification will boost up your resume.
You will learn the researched and proven approach adopted by successful people to transform their careers.
You will be able to incorporate various techniques successfully and understand your customers better.
 Requirements
No formal qualifications required, anyone from any academic background can take this course.
Access to a computer or digital device with internet connectivity.
Course Curriculum
Module 01: Introduction to GCSE English			
▶	Introduction to GCSE English	🕐 00:11:00
Module 02: Edexcel English Section A Part 01			
▶	Edexcel English Section A Part 01	🕐 00:17:00
Module 03: Edexcel English Section A Part 02			
▶	Edexcel English Section A Part 02	🕐 00:17:00
Module 04: Edexcel English Section B			
	Edexcel English Section B	🕐 00:20:00
Module 05: Edexcel English Section C			
▶	Edexcel English Section C	🕐 00:18:00
Module 06: Cambridge English Exercise 1-4			
▶	Cambridge English Exercise 1-4	🕐 00:22:00
Module 07: Cambridge English Exercise 5			
▶	Cambridge English Exercise 5	🕐 00:13:00
Module 08: Cambridge English Exercise 6			
▶	Cambridge English Exercise 6	🕐 00:13:00
Module 09: Basics of Grammar Part 01			
▶	Basics of Grammar Part 01	🕐 00:10:00
Module 10: Basics of Grammar Part 02			
▶	Basics of Grammar Part 02	🕐 00:10:00
Module 11: The Basics of Sentences			
▶	The Basics of Sentences	🕐 00:09:00
Module 12: Structure of Sentences			
▶	Structure of Sentences	🕐 00:10:00
Module 13: English Language Reading Part 01			
▶	English Language Reading Part 01	🕐 00:10:00
Module 14: English Language Reading Part 02			
▶	English Language Reading Part 02	🕐 00:14:00
Module 15: English Academic Writing Part 01			
▶	English Academic Writing Part 01	🕐 00:10:00
Module 16: English Academic Writing Part 02			
▶	English Academic Writing Part 02	🕐 00:12:00
Module 17: Punctuation and Capitalisation in Writing			
▶	Punctuation and Capitalization in Writing	🕐 00:12:00
Module 18: Most Common Mistakes and How to Avoid Them			
▶	Most Common Mistakes and How to Avoid Them	🕐 00:13:00
Module 19: Cambridge English Listening			
▶	Cambridge English Listening	🕐 00:11:00
Module 20: Cambridge English Speaking			
▶	Cambridge English Speaking	🕐 00:11:00
Assignment			
	Assignment - GCSE English	🕐 05:01:00

English Language Teaching

GCSE

English for Academic Purposes (EAP)

GCSE English

Certificate in Advanced English (CAE)

General English

Gain the skills and credentials to kick start a successful career and learn from the experts with this

<p fr-original-style="" id="isPasted" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Discover the wonders of our planet and our role within it through our A-Level Geography course, specifically designed for self-paced learning. Gain deeper insights into the marvels and challenges our world faces from diverse landscapes to human interactions and the subsequent consequences on nature.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Venture on a virtual journey exploring various terrains from arid deserts to dynamic glaciers, and lively coastal systems. Delve into the pressing issues of environmental stress on ecosystems, urban development implications, and the complex threads of globalisation.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Master the art of collecting, processing, and interpreting valuable information using both qualitative and quantitative methods. You&rsquo;ll become proficient in contextualisation and reporting, demonstrating a strong understanding of fieldwork through independent research projects.</p><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; user-select: none; break-after: page; box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This course adheres to the latest Cambridge International A-Level Geography syllabus, offering a streamlined and engaging online learning experience. Benefit from unlimited tutor support, well-structured assignments, and a clear induction to equip you with the skills and knowledge for exam preparation. If you&rsquo;re in the UK, you can avail our guaranteed exam centre access for your final A-Level examinations.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Your enrolment comes with the following benefits:</strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"> Access to a brand-new course, with content that is dynamic, engaging and tailored to the latest specification</li><li fr-original-style="" style="box-sizing: border-box;"> Fast track options for exams in 2022</li><li fr-original-style="" style="box-sizing: border-box;"> Exam pass guarantee &ndash; We&#39;ll support you to your next exam for free if you don&rsquo;t pass the first time</li><li fr-original-style="" style="box-sizing: border-box;"> Guaranteed exam venue access &ndash; Explore our network of partnership exam centres</li><li fr-original-style="" style="box-sizing: border-box;"> Unlimited tutor support &ndash; Benefit from personalised study planning and comprehensive support throughout your learning journey</li></ul><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; user-select: none; break-after: page; box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Geography extends beyond the textbook. It&#39;s about understanding our planet, recognising our responsibilities towards it, and expanding our knowledge on how human activities shape and change our environment.</p><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; user-select: none; break-after: page; box-sizing: border-box;"><h3 fr-original-style="" id="isPasted" style="box-sizing: border-box;">&nbsp;About the awarding body</h3><ul fr-original-style="color: rgb(0, 0, 0);" style="color: rgb(0, 0, 0); box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Awarding body:</strong>&nbsp;Cambridge Assessment International Education (CAIE)</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Our course code:</strong> X923</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Qualification code:</strong> 9696</li></ul><p fr-original-style=" color: rgb(0, 0, 0);" style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;">Cambridge Assessment International Education is the world&rsquo;s largest provider of international education programmes, qualifications and exams, delivering assessments to over 8 million learners in over 170 countries.</p><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; user-select: none; break-after: page; box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">⏱ Study Hours:</strong> Allow 250-300 hours of study time plus additional time for assignments.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">👩&zwj;🏫 Study Method:</strong> Engage with a variety of media such as videos, quizzes, and interactive activities via our online platform. Learning resources can also be printed for convenience.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">📆 Course Duration: </strong>Your enrolment lasts up to 24 months from the date of registration.&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">📋 Assessment:</strong> Enrol now for Summer 2022 examinations. You&#39;ll need to complete four standard A-Level written exams with a blend of short and long answer questions, and extended response questions. We also provide guaranteed exam space across the UK and a repeat exam support. Additionally, various assignments throughout the course will help gauge your progress and generate predicted grades if needed.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">👩&zwj;🎓 Course Outcomes:</strong> On successful completion, you&#39;ll receive an A-Level in Geography, issued by Cambridge International, identical to that received by students at any other institution. This syllabus (9696) is selected by Oxbridge for its suitability to distance learning.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">ℹ️ Additional Information: </strong>Difficulty - Level 3; Entry requirements - A GCSE or equivalent in Geography is recommended; UCAS Points - 56</p><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; user-select: none; break-after: page; box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Content: </strong>Explore a wide range of topics such as hydrology, fluvial geomorphology, atmosphere and weather, rocks and weathering, population dynamics, migration and settlement, tropical and hazardous environments, production, location, and global interdependence. Each unit explores its topic in-depth, providing a comprehensive understanding of the intricacies of physical and human geography.</p>

Discover the wonders of our planet and our role within it through our A-Level Geography course, specifically designed for self-paced learning. Gain deeper insights into the marvels and challenges our world faces from diverse landscapes to human interactions and the subsequent consequences on nature.
Venture on a virtual journey exploring various terrains from arid deserts to dynamic glaciers, and lively coastal systems. Delve into the pressing issues of environmental stress on ecosystems, urban development implications, and the complex threads of globalisation.
Master the art of collecting, processing, and interpreting valuable information using both qualitative and quantitative methods. You’ll become proficient in contextualisation and reporting, demonstrating a strong understanding of fieldwork through independent research projects.



This course adheres to the latest Cambridge International A-Level Geography syllabus, offering a streamlined and engaging online learning experience. Benefit from unlimited tutor support, well-structured assignments, and a clear induction to equip you with the skills and knowledge for exam preparation. If you’re in the UK, you can avail our guaranteed exam centre access for your final A-Level examinations.
Your enrolment comes with the following benefits:
Access to a brand-new course, with content that is dynamic, engaging and tailored to the latest specification
Fast track options for exams in 2022
Exam pass guarantee – We'll support you to your next exam for free if you don’t pass the first time
Guaranteed exam venue access – Explore our network of partnership exam centres
Unlimited tutor support – Benefit from personalised study planning and comprehensive support throughout your learning journey



Geography extends beyond the textbook. It's about understanding our planet, recognising our responsibilities towards it, and expanding our knowledge on how human activities shape and change our environment.



 About the awarding body
Awarding body: Cambridge Assessment International Education (CAIE)
Our course code: X923
Qualification code: 9696
Cambridge Assessment International Education is the world’s largest provider of international education programmes, qualifications and exams, delivering assessments to over 8 million learners in over 170 countries.



⏱ Study Hours: Allow 250-300 hours of study time plus additional time for assignments.
👩‍🏫 Study Method: Engage with a variety of media such as videos, quizzes, and interactive activities via our online platform. Learning resources can also be printed for convenience.
📆 Course Duration: Your enrolment lasts up to 24 months from the date of registration. 
📋 Assessment: Enrol now for Summer 2022 examinations. You'll need to complete four standard A-Level written exams with a blend of short and long answer questions, and extended response questions. We also provide guaranteed exam space across the UK and a repeat exam support. Additionally, various assignments throughout the course will help gauge your progress and generate predicted grades if needed.
👩‍🎓 Course Outcomes: On successful completion, you'll receive an A-Level in Geography, issued by Cambridge International, identical to that received by students at any other institution. This syllabus (9696) is selected by Oxbridge for its suitability to distance learning.
ℹ️ Additional Information: Difficulty - Level 3; Entry requirements - A GCSE or equivalent in Geography is recommended; UCAS Points - 56



Course Content: Explore a wide range of topics such as hydrology, fluvial geomorphology, atmosphere and weather, rocks and weathering, population dynamics, migration and settlement, tropical and hazardous environments, production, location, and global interdependence. Each unit explores its topic in-depth, providing a comprehensive understanding of the intricacies of physical and human geography.

Oxbridge

A Level Geography

A-Levels Geography Distance Learning Course by Oxbridge

General admission

<h3><b>Overview</b></h3>
<p><b>Uplift Your Career &amp; Skill Up to Your Dream Job - Learning Simplified From Home!</b></p>
<p><span>Kickstart your career &amp; boost your employability by helping you discover your skills, talents and interests with our special </span><b>GCSE English </b><span>Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today's workplaces.</span></p>
<p><span>The </span><b>GCSE English </b><span>Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This </span><b>GCSE English </b><span>Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field.</span></p>
<p><span>This </span><b>GCSE English </b><span>Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly.</span></p>
<p><span>At StudyHub, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from StudyHub, you get unlimited Lifetime access with 24/7 dedicated tutor support.</span></p>
<div><b>Why Choose This Course</b></div>
<ul>
<li>Unlimited access to the course for a lifetime.</li>
<li>Opportunity to earn a certificate accredited by the <b>CPD Quality Standards</b> and <b>CIQ </b>after completing this course.</li>
<li>Structured lesson planning in line with industry standards.</li>
<li>Immerse yourself in innovative and captivating course materials and activities.</li>
<li>Assessments designed to evaluate advanced cognitive abilities and skill proficiency.</li>
<li>Flexibility to complete the Course at your own pace, on your own schedule.</li>
<li>Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience.</li>
<li>Unlock career resources for CV improvement, interview readiness, and job success.</li>
</ul>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials of the </span><b>GCSE English</b><span> there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99. Original Hard Copy certificates need to be ordered at an additional cost of £8.</span></p>
<h3><b>Who is this course for?</b></h3>
<p><span>This </span><b>GCSE English</b><span> course is ideal for</span></p>
<ul>
<li><span>Students</span></li>
<li><span>Recent graduates</span></li>
<li><span>Job Seekers</span></li>
<li><span>Anyone interested in this topic</span></li>
<li><span>People already working in the relevant fields and want to polish their knowledge and skill.</span></li>
</ul>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>GCSE English</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning.This </span><b>GCSE English</b><span> was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.</span></p>
<h3><b>Career path</b></h3>
<p><span>As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This </span><b>GCSE English </b><span>is a great way for you to gain multiple skills from the comfort of your home.</span></p><div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4">Module 01: Introduction to GCSE English</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to GCSE English</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 02: Edexcel English Section A Part 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Edexcel English Section A Part 01</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 03: Edexcel English Section A Part 02</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Edexcel English Section A Part 02</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 04: Edexcel English Section B</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Edexcel English Section B</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 05: Edexcel English Section C</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Edexcel English Section C</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 06: Cambridge English Exercise 1-4</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Exercise 1-4</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 07: Cambridge English Exercise 5</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Exercise 5</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 08: Cambridge English Exercise 6</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Exercise 6</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 09: Basics of Grammar Part 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Basics of Grammar Part 01</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 10: Basics of Grammar Part 02</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Basics of Grammar Part 02</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 11: The Basics of Sentences</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Basics of Sentences</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 12: Structure of Sentences</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Structure of Sentences</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 13: English Language Reading Part 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>English Language Reading Part 01</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 14: English Language Reading Part 02</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>English Language Reading Part 02</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 15: English Academic Writing Part 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>English Academic Writing Part 01</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 16: English Academic Writing Part 02</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>English Academic Writing Part 02</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 17: Punctuation and Capitalisation in Writing</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Punctuation and Capitalisation in Writing</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 18: Most Common Mistakes and How to Avoid Them</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Most Common Mistakes and How to Avoid Them</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 19: Cambridge English Listening</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Listening</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 20: Cambridge English Speaking</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Speaking</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Overview
Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home!
Kickstart your career & boost your employability by helping you discover your skills, talents and interests with our special GCSE English Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today's workplaces.
The GCSE English Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This GCSE English Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field.
This GCSE English Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly.
At StudyHub, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from StudyHub, you get unlimited Lifetime access with 24/7 dedicated tutor support.
Why Choose This Course
Unlimited access to the course for a lifetime.
Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course.
Structured lesson planning in line with industry standards.
Immerse yourself in innovative and captivating course materials and activities.
Assessments designed to evaluate advanced cognitive abilities and skill proficiency.
Flexibility to complete the Course at your own pace, on your own schedule.
Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience.
Unlock career resources for CV improvement, interview readiness, and job success.
Certification
After studying the course materials of the GCSE English there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99. Original Hard Copy certificates need to be ordered at an additional cost of £8.
Who is this course for?
This GCSE English course is ideal for
Students
Recent graduates
Job Seekers
Anyone interested in this topic
People already working in the relevant fields and want to polish their knowledge and skill.
Prerequisites
This GCSE English does not require you to have any prior qualifications or experience. You can just enrol and start learning.This GCSE English was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.
Career path
As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This GCSE English is a great way for you to gain multiple skills from the comfort of your home.
 Course Curriculum

Module 01: Introduction to GCSE English			
	Introduction to GCSE English		00:11:00
Module 02: Edexcel English Section A Part 01			
	Edexcel English Section A Part 01		00:16:00
Module 03: Edexcel English Section A Part 02			
	Edexcel English Section A Part 02		00:17:00
Module 04: Edexcel English Section B			
	Edexcel English Section B		00:20:00
Module 05: Edexcel English Section C			
	Edexcel English Section C		00:18:00
Module 06: Cambridge English Exercise 1-4			
	Cambridge English Exercise 1-4		00:22:00
Module 07: Cambridge English Exercise 5			
	Cambridge English Exercise 5		00:13:00
Module 08: Cambridge English Exercise 6			
	Cambridge English Exercise 6		00:13:00
Module 09: Basics of Grammar Part 01			
	Basics of Grammar Part 01		00:10:00
Module 10: Basics of Grammar Part 02			
	Basics of Grammar Part 02		00:10:00
Module 11: The Basics of Sentences			
	The Basics of Sentences		00:09:00
Module 12: Structure of Sentences			
	Structure of Sentences		00:10:00
Module 13: English Language Reading Part 01			
	English Language Reading Part 01		00:10:00
Module 14: English Language Reading Part 02			
	English Language Reading Part 02		00:14:00
Module 15: English Academic Writing Part 01			
	English Academic Writing Part 01		00:10:00
Module 16: English Academic Writing Part 02			
	English Academic Writing Part 02		00:12:00
Module 17: Punctuation and Capitalisation in Writing			
	Punctuation and Capitalisation in Writing		00:12:00
Module 18: Most Common Mistakes and How to Avoid Them			
	Most Common Mistakes and How to Avoid Them		00:13:00
Module 19: Cambridge English Listening			
	Cambridge English Listening		00:11:00
Module 20: Cambridge English Speaking			
	Cambridge English Speaking		00:11:00

Studyhub UK

Teaching English

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				<p>Register on the GCSE English today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career.</p><p>The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials.</p><p>Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as proof of your course completion.</p><p>The GCSE English is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones.</p><p>The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly!</p>					</div>
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			<h2>What You Get With The Course</h2>		</div>
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					<ul>
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										<span>Receive a e-certificate upon successful completion of the course</span>
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										<span>Get taught by experienced, professional instructors</span>
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										<span>Study at a time and pace that suits your learning style</span>
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										<span>Get instant feedback on assessments </span>
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										<span>24/7 help and advice via email or live chat</span>
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											<span>
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										<span>Get full tutor support on weekdays (Monday to Friday)</span>
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			<h2>Course Design</h2>		</div>
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				<span>The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.</span>

You are taught through a combination of
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										<span>Video lessons</span>
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										<span>Online study materials</span>
									</li>
						</ul>
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			<h2>Certificate of Achievement</h2>		</div>
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				<div id="course-home"><div><h5><b>CPD Certificate of Achievement from Janets</b></h5><p><span>Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99.</span></p></div></div>					</div>
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			<h2>Who Is This Course For:</h2>		</div>
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				<div id="course-home"><div><p>The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.</p></div></div>					</div>
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			<h2>Requirements:</h2>		</div>
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				<p>The online training is open to all students and has no formal entry requirements. To study the GCSE English, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.</p>					</div>
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				<h3>Course Content</h3>

<div id="course_curriculum">
<table width="100%">				<tbody><tr>
					<td colspan="4">Module 01: Introduction to GCSE English</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to GCSE English</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 02: Edexcel English Section A Part 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Edexcel English Section A Part 01</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 03: Edexcel English Section A Part 02</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Edexcel English Section A Part 02</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 04: Edexcel English Section B</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Edexcel English Section B</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 05: Edexcel English Section C</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Edexcel English Section C</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 06: Cambridge English Exercise 1-4</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Exercises 1-4</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 07: Cambridge English Exercise 5</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Exercise 5</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 08: Cambridge English Exercise 6</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Exercise 6</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 09: Basics of Grammar Part 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Basics of Grammar Part 01</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 10: Basics of Grammar Part 02</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Basics of Grammar Part 02</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 11: The Basics of Sentences</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Basics of Sentences</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 12: Structure of Sentences</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Structure of Sentences</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 13: English Language Reading Part 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>English Language Reading Part 01</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 14: English Language Reading Part 02</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>English Language Reading Part 02</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 15: English Academic Writing Part 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>English Academic Writing Part 01</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 16: English Academic Writing Part 02</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>English Academic Writing Part 02</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 17: Punctuation and Capitalisation in Writing</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Punctuation and Capitalisation in Writing</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 18: Most Common Mistakes and How to Avoid Them</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Most Common Mistakes and How to Avoid Them</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 19: Cambridge English Listening</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Listening</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 20: Cambridge English Speaking</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cambridge English Speaking</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
				</tbody></table></div>

			</div>
			<h2>Frequently Asked Questions</h2>
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                                <span>
                                    Are there any prerequisites for taking the course?
                                </span>
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                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        There are no specific prerequisites for this course, nor
                                        are there any formal entry requirements. All you need is
                                        an internet connection, a good understanding of English
                                        and a passion for learning for this course.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Can I access the course at any time, or is there a set
                                    schedule?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
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                                    <p>
                                        You have the flexibility to access the course at any time
                                        that suits your schedule. Our courses are self-paced,
                                        allowing you to study at your own pace and convenience.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    How long will I have access to the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        For this course, you will have access to the course
                                        materials for 1 year only. This means you can review the
                                        content as often as you like within the year, even after
                                        you've completed the course. However, if you buy Lifetime
                                        Access for the course, you will be able to access the
                                        course for a lifetime.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Is there a certificate of completion provided after
                                    completing the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        Yes, upon successfully completing the course, you will
                                        receive a certificate of completion. This certificate can
                                        be a valuable addition to your professional portfolio and
                                        can be shared on your various social networks.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Can I switch courses or get a refund if I'm not satisfied
                                    with the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
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                                    <p>
                                        We want you to have a positive learning experience. If
                                        you're not satisfied with the course, you can request a
                                        course transfer or refund within 14 days of the initial
                                        purchase.
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                                    How do I track my progress in the course?
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                                        Our platform provides tracking tools and progress
                                        indicators for each course. You can monitor your progress,
                                        completed lessons, and assessments through your learner
                                        dashboard for the course.
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                                    What if I have technical issues or difficulties with the
                                    course?
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                                        If you encounter technical issues or content-related
                                        difficulties with the course, our support team is
                                        available to assist you. You can reach out to them for
                                        prompt resolution.
                                    </p>
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                            </div>
                        </div>

Register on the GCSE English today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career.
The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials.
Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as proof of your course completion.
The GCSE English is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones.
The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly!
What You Get With The Course
Receive a e-certificate upon successful completion of the course
Get taught by experienced, professional instructors
Study at a time and pace that suits your learning style
Get instant feedback on assessments
24/7 help and advice via email or live chat
Get full tutor support on weekdays (Monday to Friday)
Course Design
The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of
Video lessons
Online study materials
Certificate of Achievement
CPD Certificate of Achievement from Janets
Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99.
Who Is This Course For:
The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.
Requirements:
The online training is open to all students and has no formal entry requirements. To study the GCSE English, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.
Course Content
Module 01: Introduction to GCSE English			
	Introduction to GCSE English		00:11:00
Module 02: Edexcel English Section A Part 01			
	Edexcel English Section A Part 01		00:16:00
Module 03: Edexcel English Section A Part 02			
	Edexcel English Section A Part 02		00:17:00
Module 04: Edexcel English Section B			
	Edexcel English Section B		00:20:00
Module 05: Edexcel English Section C			
	Edexcel English Section C		00:18:00
Module 06: Cambridge English Exercise 1-4			
	Cambridge English Exercises 1-4		00:22:00
Module 07: Cambridge English Exercise 5			
	Cambridge English Exercise 5		00:13:00
Module 08: Cambridge English Exercise 6			
	Cambridge English Exercise 6		00:13:00
Module 09: Basics of Grammar Part 01			
	Basics of Grammar Part 01		00:10:00
Module 10: Basics of Grammar Part 02			
	Basics of Grammar Part 02		00:10:00
Module 11: The Basics of Sentences			
	The Basics of Sentences		00:09:00
Module 12: Structure of Sentences			
	Structure of Sentences		00:10:00
Module 13: English Language Reading Part 01			
	English Language Reading Part 01		00:10:00
Module 14: English Language Reading Part 02			
	English Language Reading Part 02		00:14:00
Module 15: English Academic Writing Part 01			
	English Academic Writing Part 01		00:10:00
Module 16: English Academic Writing Part 02			
	English Academic Writing Part 02		00:12:00
Module 17: Punctuation and Capitalisation in Writing			
	Punctuation and Capitalisation in Writing		00:12:00
Module 18: Most Common Mistakes and How to Avoid Them			
	Most Common Mistakes and How to Avoid Them		00:13:00
Module 19: Cambridge English Listening			
	Cambridge English Listening		00:11:00
Module 20: Cambridge English Speaking			
	Cambridge English Speaking		00:11:00
Frequently Asked Questions
Are there any prerequisites for taking the course?
 There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. 
Can I access the course at any time, or is there a set schedule?
 You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. 
How long will I have access to the course?
 For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. 
Is there a certificate of completion provided after completing the course?
 Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. 
Can I switch courses or get a refund if I'm not satisfied with the course?
 We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. 
How do I track my progress in the course?
 Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. 
What if I have technical issues or difficulties with the course?
 If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution. 

Janets

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			<h2>Overview
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					<p>This comprehensive course on <strong>GCSE English </strong>will deepen your understanding on this topic.</p><p>After successful completion of this course you can acquire the required skills in this sector. This <strong>GCSE English </strong> comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.   </p><p>So enrol in this course today to fast-track your career ladder.</p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p>You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.</p>					</div>
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			<h2>Who is This course for?</h2>		</div>
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					<p>There is no experience or previous qualifications required for enrolment on this <strong>GCSE English</strong>. It is available to all students, of all academic backgrounds.</p>					</div>
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			<h2>Requirements</h2>		</div>
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					<p>Our <strong>GCSE English</strong> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</p><p>There is no time limit for completing this course, it can be studied in your own time at your own pace.</p>					</div>
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			<h2>Career Path</h2>		</div>
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					<p>Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to-</p><ul><li>Open doors of opportunities</li><li>Increase your adaptability</li><li>Keep you relevant</li><li>Boost confidence</li></ul><p>And much more!</p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>20 sections • 20 lectures • 04:22:00 total length</p></div><div><div><div><div><div><div><div><p>•Introduction to GCSE English: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Edexcel English Section A Part 01: 00:16:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Edexcel English Section A Part 02: 00:17:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Edexcel English Section B: 00:20:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Edexcel English Section C: 00:18:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Cambridge English Exercise 1-4: 00:22:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Cambridge English Exercise 5: 00:13:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Cambridge English Exercise 6: 00:13:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Basics of Grammar Part 01: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Basics of Grammar Part 02: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•The Basics of Sentences: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Structure of Sentences: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•English Language Reading Part 01: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•English Language Reading Part 02: 00:14:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•English Academic Writing Part 01: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•English Academic Writing Part 02: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Punctuation and Capitalisation in Writing: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Most Common Mistakes and How to Avoid Them: 00:13:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Cambridge English Listening: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Cambridge English Speaking: 00:11:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Overview

This comprehensive course on GCSE English will deepen your understanding on this topic.
After successful completion of this course you can acquire the required skills in this sector. This GCSE English  comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. 
So enrol in this course today to fast-track your career ladder.
How will I get my certificate?
You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.
Who is This course for?
There is no experience or previous qualifications required for enrolment on this GCSE English. It is available to all students, of all academic backgrounds.
Requirements
Our GCSE English is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.
There is no time limit for completing this course, it can be studied in your own time at your own pace.
Career Path
Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to-
Open doors of opportunities
Increase your adaptability
Keep you relevant
Boost confidence
And much more!
Course Curriculum
20 sections • 20 lectures • 04:22:00 total length
•Introduction to GCSE English: 00:11:00
•Edexcel English Section A Part 01: 00:16:00
•Edexcel English Section A Part 02: 00:17:00
•Edexcel English Section B: 00:20:00
•Edexcel English Section C: 00:18:00
•Cambridge English Exercise 1-4: 00:22:00
•Cambridge English Exercise 5: 00:13:00
•Cambridge English Exercise 6: 00:13:00
•Basics of Grammar Part 01: 00:10:00
•Basics of Grammar Part 02: 00:10:00
•The Basics of Sentences: 00:09:00
•Structure of Sentences: 00:10:00
•English Language Reading Part 01: 00:10:00
•English Language Reading Part 02: 00:14:00
•English Academic Writing Part 01: 00:10:00
•English Academic Writing Part 02: 00:12:00
•Punctuation and Capitalisation in Writing: 00:12:00
•Most Common Mistakes and How to Avoid Them: 00:13:00
•Cambridge English Listening: 00:11:00
•Cambridge English Speaking: 00:11:00

Apex Learning

Professional Skills Course (PSC)

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			<h2>Overview of GCSE English Preparation Online</h2>		</div>
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					<div><p><span>Join our GCSE English Preparation Online course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The GCSE English Preparation Online course has everything you need to get a great start in this sector.</span></p><p><span>Improving and moving forward is key to getting ahead personally. The GCSE English Preparation Online course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now!</span></p></div>
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			<h3>Get a Quick Look at The Course Content:</h3>		</div>
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			<h3>This <span>GCSE English Preparation Online</span> Course will help you to learn:</h3>		</div>
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										<span>Hone your skills to help you advance your career.</span>
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										<span>Acquire a comprehensive understanding of various topics and tips.</span>
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										<span>Learn in-demand skills that are in high demand among UK employers</span>
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					<div><p><span>This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this GCSE English Preparation Online. Enrol today and complete the course to achieve a certificate that can change your career forever.</span></p></div>
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			<h2>Details</h2>		</div>
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			<h3>Perks of Learning with IOMH</h3>		</div>
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										<span>Study Online - Whenever and Wherever You Want.</span>
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										<span>Instant Digital/ PDF Certificate.</span>
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										<span>100% Money Back Guarantee.</span>
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										<span>12 Months Access.</span>
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			<h3>Process of Evaluation</h3>		</div>
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					<div><p>After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate.</p></div>
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			<h3>Certificate of Achievement</h3>		</div>
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					<div><h4><span>Certificate of Completion - Digital / PDF Certificate</span></h4>  
<p>After completing the <span>GCSE English Preparation Online course</span>, you can order your<span> CPD Accredited Digital / PDF Certificate for £5.99. </span></p>
<p><span>Certificate of Completion - Hard copy Certificate</span></p>
<p><span>You can get the CPD Accredited <b><i>Hard Copy Certificate for £12.99</i></b>.</span></p>
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<div><span>Shipping Charges:</span><span><span><br /></span></span></div>
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<li><p><span>Inside the UK: £3.99</span></p></li>
<li><p><span>International: £10.99</span></p></li>
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			<h3>Who Is This Course for?</h3>		</div>
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					<div><p><span>This GCSE English Preparation Online is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. </span></p><p><span>On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. </span></p><p><span>This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education.</span></p></div>
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			<h3>Requirements</h3>		</div>
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					<div><p><span>You don't need any educational qualification or experience to enrol in the GCSE English Preparation Online course.</span></p>
<p><span>Do note: you must be at least 16 years old to enrol.</span></p>
<p><span>Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course.</span></p></div>
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			<h3>Career Path</h3>		</div>
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					<div><p><span>The certification and skills you get from this </span><span>GCSE English Preparation Online Course</span><span> can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors.</span></p></div>
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												Q. How do I purchase a course?
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					<div id="elementor-tab-content-2071"><p>1.  You need to find the right course on our IOMH website at first. You can search for any course or find the course from the Courses section of our website.<br />2. Click on Take This Course button, and you will be directed to the Cart page.<br />3. You can update the course quantity and also remove any unwanted items in the CART and after that click on the Checkout option and enter your billing details.<br />4. Once the payment is made, you will receive an email with the login credentials, and you can start learning after logging into the portal.</p></div>
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												Q. I have purchased the course when will I be able to access the materials?
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												Q. I haven't received my certificate yet. What should I do?
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					<div id="elementor-tab-content-2073"><p>You should receive your Digital Certificate within 24 hours after placing the order, and it will take 3-9 days to deliver the hard copies to your address if you are in the UK.</p><p>For International Delivery, it will take 20-25 days.</p><p>If you require any assistance, get in touch with our dedicated Customer Support team, and your queries/issues will be dealt with accordingly.</p></div>
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												Q. I don't have a credit/debit card, what other methods of payment do you accept?
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					<div id="elementor-tab-content-2074"><p>You can make the payment using PayPal or you can Bank Transfer the amount.</p><p>For Bank transfer you will require an invoice from us and you need to contact our Customer Support team and provide details of your purchase to get the invoice.</p><p>After that, you will receive an email with the invoice and bank details and you can make the payment accordingly.</p></div>
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												Q. Can I do the courses from outside UK?
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					<div id="elementor-tab-content-2075"><p>We are an online course provider, and learners from anywhere in the world can enrol on our courses using an internet-connected device.</p></div>
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												Q. When I log into the account it says 'Contact Administrator'.
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					<div id="elementor-tab-content-2076"><p>To resolve this issue, please log out of your account and then log back in.</p></div>
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				<h3>
	<span>Course Curriculum</span>
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<table>				<tbody><tr>
					<td colspan="4">Module 01: Introduction to GCSE English</td>
				</tr>
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					<td><i></i></td>
					<td>Introduction to GCSE English</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
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					<td colspan="4">Module 02: Edexcel English Section A Part 01</td>
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					<td><i></i></td>
					<td>Edexcel English Section A Part 01</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
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					<td colspan="4">Module 03: Edexcel English Section A Part 02</td>
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					<td><i></i></td>
					<td>Edexcel English Section A Part 02</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
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					<td colspan="4">Module 04: Edexcel English Section B</td>
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					<td><i></i></td>
					<td>Edexcel English Section B</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
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					<td colspan="4">Module 05: Edexcel English Section C</td>
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					<td><i></i></td>
					<td>Edexcel English Section C</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
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					<td colspan="4">Module 06: Cambridge English Exercise 1-4</td>
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					<td><i></i></td>
					<td>Cambridge English Exercise 1-4</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
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					<td colspan="4">Module 07: Cambridge English Exercise 5</td>
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					<td><i></i></td>
					<td>Cambridge English Exercise 5</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
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					<td colspan="4">Module 08: Cambridge English Exercise 6</td>
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					<td>Cambridge English Exercise 6</td>
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					<td><span><i></i> 00:13:00</span></td>
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					<td colspan="4">Module 09: Basics of Grammar Part 01</td>
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					<td>Basics of Grammar Part 01</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
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					<td colspan="4">Module 10: Basics of Grammar Part 02</td>
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					<td><i></i></td>
					<td>Basics of Grammar Part 02</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
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					<td colspan="4">Module 11: The Basics of Sentences</td>
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					<td><i></i></td>
					<td>The Basics of Sentences</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
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					<td colspan="4">Module 12: Structure of Sentences</td>
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					<td><i></i></td>
					<td>Structure of Sentences</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
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					<td colspan="4">Module 13: English Language Reading Part 01</td>
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					<td><i></i></td>
					<td>English Language Reading Part 01</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
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					<td colspan="4">Module 14: English Language Reading Part 02</td>
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					<td><i></i></td>
					<td>English Language Reading Part 02</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
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					<td colspan="4">Module 15: English Academic Writing Part 01</td>
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					<td><i></i></td>
					<td>English Academic Writing Part 01</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
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					<td colspan="4">Module 16: English Academic Writing Part 02</td>
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					<td><i></i></td>
					<td>English Academic Writing Part 02</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
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					<td colspan="4">Module 17: Punctuation and Capitalisation in Writing</td>
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					<td>Punctuation and Capitalisation in Writing</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
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					<td colspan="4">Module 18: Most Common Mistakes and How to Avoid Them</td>
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					<td>Most Common Mistakes and How to Avoid Them</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
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					<td colspan="4">Module 19: Cambridge English Listening</td>
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					<td><i></i></td>
					<td>Cambridge English Listening</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
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					<td colspan="4">Module 20: Cambridge English Speaking</td>
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					<td><i></i></td>
					<td>Cambridge English Speaking</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
				</tbody></table></div>

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Overview of GCSE English Preparation Online
In today’s competitive academic environment, mastering GCSE English is crucial for success. With over 5 million students sitting GCSE exams annually in the UK, the demand for effective English skills is higher than ever. Our GCSE English Preparation Online is designed to provide a comprehensive foundation in all aspects of the curriculum, ensuring that students are well-prepared for their exams.
This course covers everything from the basics of grammar and sentence structure to the intricacies of academic writing. You’ll explore different sections of the Edexcel and Cambridge English exams, enhancing your reading, writing, listening, and speaking skills. Each module is tailored to help you avoid common mistakes, improve your grammar, and master the art of effective communication.
Whether you’re a student aiming for top grades, a non-native speaker looking to improve your English, or an adult learner wishing to enhance your language skills, this course offers the tools and knowledge you need. Join us on this journey to excel in GCSE English and open doors to a brighter academic and professional future.
Become proficient in GCSE English Preparation Online Course by grasping all the essential knowledge from our top-quality course step by step. Enrol now to ensure that your GCSE English Preparation Online Course mastery is not limited to only conceptual frameworks! This GCSE English Preparation Online Course will assist you in standing out from the crowd and being more efficient in your chosen area of expertise. Furthermore, if you require assistance with the GCSE English Preparation Online Course, we will provide experts who will support and guide you. So, add this GCSE English Preparation Online Course to your cart and boost your personal and career development.
In this GCSE English Preparation Online Course, you will:
Sharpen your skills to help you advance your career.
Acquire a comprehensive understanding of various related topics and tips from industry experts.
Learn in-demand knowledge and skills in high demand among UK employers, which will help to kickstart your GCSE English Preparation Online Course career.
Enrolling in the GCSE English Preparation Online Course can assist you in getting into your desired career faster than you ever imagined. So, without further ado, start now!
Details
Perks of Learning with IOMH
One-To-One Support from a Dedicated Tutor Throughout Your Course.
Study Online - Whenever and Wherever You Want.
Instant Digital/ PDF Certificate.
100% Money Back Guarantee.
12 Months Access.
Process of Evaluation
After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate.
Certificate of Achievement
Certificate of Completion - Digital / PDF Certificate
After completing the GCSE English Preparation Online course, you can order your CPD Accredited Digital / PDF Certificate for £5.99. 
Certificate of Completion - Hard copy Certificate
You can get the CPD Accredited Hard Copy Certificate for £12.99.
Shipping Charges:
Inside the UK: £3.99
International: £10.99
Who Is This Course for?
This GCSE English Preparation Online is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. 
On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. 
This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education.
Requirements
You don't need any educational qualification or experience to enrol in the GCSE English Preparation Online course.
Do note: you must be at least 16 years old to enrol.
Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course.
Career Path
The certification and skills you get from this GCSE English Preparation Online Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors.

 Course Curriculum

Module 01: Introduction to GCSE English			
	Introduction to GCSE English		00:11:00
Module 02: Edexcel English Section A Part 01			
	Edexcel English Section A Part 01		00:16:00
Module 03: Edexcel English Section A Part 02			
	Edexcel English Section A Part 02		00:17:00
Module 04: Edexcel English Section B			
	Edexcel English Section B		00:20:00
Module 05: Edexcel English Section C			
	Edexcel English Section C		00:18:00
Module 06: Cambridge English Exercise 1-4			
	Cambridge English Exercise 1-4		00:22:00
Module 07: Cambridge English Exercise 5			
	Cambridge English Exercise 5		00:13:00
Module 08: Cambridge English Exercise 6			
	Cambridge English Exercise 6		00:13:00
Module 09: Basics of Grammar Part 01			
	Basics of Grammar Part 01		00:10:00
Module 10: Basics of Grammar Part 02			
	Basics of Grammar Part 02		00:10:00
Module 11: The Basics of Sentences			
	The Basics of Sentences		00:09:00
Module 12: Structure of Sentences			
	Structure of Sentences		00:10:00
Module 13: English Language Reading Part 01			
	English Language Reading Part 01		00:10:00
Module 14: English Language Reading Part 02			
	English Language Reading Part 02		00:14:00
Module 15: English Academic Writing Part 01			
	English Academic Writing Part 01		00:10:00
Module 16: English Academic Writing Part 02			
	English Academic Writing Part 02		00:12:00
Module 17: Punctuation and Capitalisation in Writing			
	Punctuation and Capitalisation in Writing		00:12:00
Module 18: Most Common Mistakes and How to Avoid Them			
	Most Common Mistakes and How to Avoid Them		00:13:00
Module 19: Cambridge English Listening			
	Cambridge English Listening		00:11:00
Module 20: Cambridge English Speaking			
	Cambridge English Speaking		00:11:00


IOMH - Institute of Mental Health

English for Specific Purposes (ESP)

English

GCSE English Preparation Online

<p><strong> 24-Hour Knowledge Knockdown! Prices Reduced Like Never Before </strong></p><p>Feeling the squeeze of GCSEs approaching? Did you know that in the UK, <strong>55% of students find English and Maths the most challenging subjects</strong>? Don't let statistics dictate your success! This GCSE Maths and GCSE English preparation bundle is designed to equip you with the confidence and skills to ace your GCSEs and unlock a world of possibilities.</p><p>The <strong>GCSE Maths</strong> and <strong>GCSE English</strong> Preparation course bundle transcends traditional GCSE boundaries, immersing you in Functional Skills Maths and English to further enhance your numeracy and literacy skills. As part of the GCSE Maths and GCSE English Preparation journey, you will also delve into the world of GCSE ICT, exploring Network Essentials in a way that makes sense to the digital-savvy learner of today.</p><p>Moreover, as a unique value-addition, this GCSE Maths and GCSE English Preparation bundle offers Time Management &amp; Productivity Training, to help you excel in your GCSE subjects.</p><p><strong>Courses Are Included in this GCSE Maths and GCSE English Preparation - CPD Certified Bundle: </strong></p><ul><li><strong>Course 01: GCSE English Preparation</strong></li><li><strong>Course 02: IGCSE Maths Preparation</strong></li><li><strong>Course 03: Functional Skills Maths </strong></li><li><strong>Course 04: IGCSE ICT: Network Essentials</strong></li><li><strong>Course 05: Functional Skills English</strong></li></ul><p><strong>Don't let exam anxieties hold you back. Take control of your future and enrol in this course today!</strong></p><p><strong>Learning Objectives of GCSE Maths and GCSE English Preparation :</strong></p><ul><li>Develop a strong foundational understanding of GCSE English and GCSE Maths.</li><li>Enhance functional skills in Maths and English, complementing your GCSE study plan.</li><li>Gain theoretical insights into GCSE ICT, focusing on Network Essentials, and enriching your GCSE curriculum.</li><li>Understand how to manage time and increase productivity, optimising your study habits for GCSE success.</li><li>Develop effective strategies for GCSE exam preparation and study planning.</li></ul><p><strong>Why Choose Us?</strong></p><ul><li>Get a <strong>Free CPD Accredited Certificate</strong> upon completion of  GCSE Maths and GCSE English</li><li>Get a <strong>free student ID card</strong> with  GCSE Maths and GCSE English Training program (£10 postal charge will be applicable for international delivery)</li><li>The  GCSE Maths and GCSE English is <strong>affordable and simple</strong> to understand</li><li>This course is <strong>entirely online, interactive lesson</strong> with voiceover audio</li><li>Get <strong>Lifetime access</strong> to the  GCSE Maths and GCSE English course materials</li><li>The  GCSE Maths and GCSE English comes with <strong>24/7 tutor support</strong></li></ul> <p>Start your learning journey straightaway!</p><p><strong>*** Course Curriculum ***</strong></p><p><strong> Course 01: GCSE English Preparation</strong></p><ul><li>Module 01: Introduction To GCSE English</li><li>Module 02: Edexcel English Section A Part 01</li><li>Module 03: Edexcel English Section A Part 02</li><li>Module 04: Edexcel English Section B</li><li>Module 05: Edexcel English Section C</li><li>Module 06: Cambridge English Exercise 1-4</li><li>Module 07: Cambridge English Exercise 5</li><li>Module 08: Cambridge English Exercise 6</li><li>Module 09: Basics Of Grammar Part 01</li><li>Module 10: Basics Of Grammar Part 02</li><li>Module 11: The Basics Of Sentences</li><li>Module 12: Structure Of Sentences</li><li>Module 13: English Language Reading Part 01</li><li>Module 14: English Language Reading Part 02</li><li>Module 15: English Academic Writing Part 01</li><li>Module 16: English Academic Writing Part 02</li><li>Module 17: Punctuation And Capitalisation In Writing</li><li>Module 18: Most Common Mistakes And How To Avoid Them</li><li>Module 19: Cambridge English Listening</li><li>Module 20: Cambridge English Speaking</li></ul><p><strong> Course 02: IGCSE Maths Preparation</strong></p><ul><li>Module 01: Introduction</li><li>Module 02: Previous Exams Solving</li><li>Module 03: 2020 Specimen Solving</li><li>Module 04: Examples Of Candidate Response In Previous Years</li><li>Module 05: Additional General Questions</li></ul><p><strong> Course 03: Functional Skills Maths</strong></p><ul><li>Integers ( Directed Numbers)</li><li>Factors And Multiples</li><li>Fractions</li><li>Simplification Rule : BODMAS</li><li>Decimal Numbers</li><li>Rational Numbers</li><li>Approximation</li><li>Estimation And Scientific Notation Or Standard Form</li><li>Percentage</li><li>Ratio And Proportion</li><li>Unitary Method And Its Applications</li><li>Profit , Loss, Discount And Tax</li></ul><p><strong>=========&gt;&gt;&gt;&gt;&gt; And 2 More Courses &lt;&lt;&lt;&lt;&lt;=========</strong></p><p><strong>How will I get my Certificate?</strong></p><p>After successfully completing the course, you will be able to order your Certificates as proof of your achievement.</p><ul><li><strong>PDF Certificate: </strong><strong>Free </strong>(Previously it was £12.99*5 = £65)</li><li><strong>CPD Hard Copy Certificate: £29.99</strong></li></ul> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        50 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This GCSE Maths and GCSE English Preparation bundle is suitable for</p><ul><li>GCSE students in need of Maths and English exam prep</li><li>Home learners and homeschoolers</li><li>Adults seeking skills refreshment</li><li>Parents supporting their children</li><li>Anyone wanting to improve maths and English skills</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise to enrol in this GCSE Maths and GCSE English Preparation.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This GCSE Maths and GCSE English Preparation bundle will allow you to kickstart or take your career in the related sector to the next stage.</p><ul><li>Higher Education</li><li>Apprenticeships</li><li>Skilled Jobs</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Digital Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><p>Upon passing the Course, you need to order a <strong>Digital Certificate</strong> for each of the courses inside this bundle as proof of your new skills that are accredited by <strong>CPD QS </strong>for Free.</p></div>
        <h4>CPD Accredited Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            £29.99
        </p>
            <div><p><em>Please note that International students have to pay an additional £10 as a shipment fee.</em></p></div>

                        </div>

24-Hour Knowledge Knockdown! Prices Reduced Like Never Before
Feeling the squeeze of GCSEs approaching? Did you know that in the UK, 55% of students find English and Maths the most challenging subjects? Don't let statistics dictate your success! This GCSE Maths and GCSE English preparation bundle is designed to equip you with the confidence and skills to ace your GCSEs and unlock a world of possibilities.
The GCSE Maths and GCSE English Preparation course bundle transcends traditional GCSE boundaries, immersing you in Functional Skills Maths and English to further enhance your numeracy and literacy skills. As part of the GCSE Maths and GCSE English Preparation journey, you will also delve into the world of GCSE ICT, exploring Network Essentials in a way that makes sense to the digital-savvy learner of today.
Moreover, as a unique value-addition, this GCSE Maths and GCSE English Preparation bundle offers Time Management & Productivity Training, to help you excel in your GCSE subjects.
Courses Are Included in this GCSE Maths and GCSE English Preparation - CPD Certified Bundle: 
Course 01: GCSE English Preparation
Course 02: IGCSE Maths Preparation
Course 03: Functional Skills Maths
Course 04: IGCSE ICT: Network Essentials
Course 05: Functional Skills English
Don't let exam anxieties hold you back. Take control of your future and enrol in this course today!
Learning Objectives of GCSE Maths and GCSE English Preparation :
Develop a strong foundational understanding of GCSE English and GCSE Maths.
Enhance functional skills in Maths and English, complementing your GCSE study plan.
Gain theoretical insights into GCSE ICT, focusing on Network Essentials, and enriching your GCSE curriculum.
Understand how to manage time and increase productivity, optimising your study habits for GCSE success.
Develop effective strategies for GCSE exam preparation and study planning.
Why Choose Us?
Get a Free CPD Accredited Certificate upon completion of GCSE Maths and GCSE English
Get a free student ID card with GCSE Maths and GCSE English Training program (£10 postal charge will be applicable for international delivery)
The GCSE Maths and GCSE English is affordable and simple to understand
This course is entirely online, interactive lesson with voiceover audio
Get Lifetime access to the GCSE Maths and GCSE English course materials
The GCSE Maths and GCSE English comes with 24/7 tutor support



Start your learning journey straightaway!
*** Course Curriculum ***
Course 01: GCSE English Preparation
Module 01: Introduction To GCSE English
Module 02: Edexcel English Section A Part 01
Module 03: Edexcel English Section A Part 02
Module 04: Edexcel English Section B
Module 05: Edexcel English Section C
Module 06: Cambridge English Exercise 1-4
Module 07: Cambridge English Exercise 5
Module 08: Cambridge English Exercise 6
Module 09: Basics Of Grammar Part 01
Module 10: Basics Of Grammar Part 02
Module 11: The Basics Of Sentences
Module 12: Structure Of Sentences
Module 13: English Language Reading Part 01
Module 14: English Language Reading Part 02
Module 15: English Academic Writing Part 01
Module 16: English Academic Writing Part 02
Module 17: Punctuation And Capitalisation In Writing
Module 18: Most Common Mistakes And How To Avoid Them
Module 19: Cambridge English Listening
Module 20: Cambridge English Speaking
Course 02: IGCSE Maths Preparation
Module 01: Introduction
Module 02: Previous Exams Solving
Module 03: 2020 Specimen Solving
Module 04: Examples Of Candidate Response In Previous Years
Module 05: Additional General Questions
Course 03: Functional Skills Maths
Integers ( Directed Numbers)
Factors And Multiples
Fractions
Simplification Rule : BODMAS
Decimal Numbers
Rational Numbers
Approximation
Estimation And Scientific Notation Or Standard Form
Percentage
Ratio And Proportion
Unitary Method And Its Applications
Profit , Loss, Discount And Tax
=========>>>>> And 2 More Courses <<<<<=========
How will I get my Certificate?
After successfully completing the course, you will be able to order your Certificates as proof of your achievement.
PDF Certificate: Free (Previously it was £12.99*5 = £65)
CPD Hard Copy Certificate: £29.99
CPD 
50 CPD hours / points  Accredited by CPD Quality Standards



Who is this course for?
This GCSE Maths and GCSE English Preparation bundle is suitable for
GCSE students in need of Maths and English exam prep
Home learners and homeschoolers
Adults seeking skills refreshment
Parents supporting their children
Anyone wanting to improve maths and English skills



Requirements 
You will not need any prior background or expertise to enrol in this GCSE Maths and GCSE English Preparation.



Career path 
This GCSE Maths and GCSE English Preparation bundle will allow you to kickstart or take your career in the related sector to the next stage.
Higher Education
Apprenticeships
Skilled Jobs



Certificates 
CPD Accredited Digital Certificate
Digital certificate - Included 
Upon passing the Course, you need to order a Digital Certificate for each of the courses inside this bundle as proof of your new skills that are accredited by CPD QS for Free.
CPD Accredited Hard Copy Certificate
Hard copy certificate - £29.99 
Please note that International students have to pay an additional £10 as a shipment fee.

Academy for Health and Fitness

Finance Cert & Exam Prep

GCSE Maths

Higher Maths

GCSE Science

GCSE Maths and GCSE English Preparation - CPD Certified

<p style="text-align: center; color: var(--text); font-size: var(--font-size); box-sizing: border-box;" fr-original-style="text-align: center;"><a href="https://www.mindmapswellbeing.com/brochure-request/" target="_blank" style="font-size: 14px; font-family: Helvetica, Arial, sans-serif; color: rgb(255, 255, 255); font-weight: bold; text-decoration: none; border-radius: 5px; background-color: rgb(61, 86, 224); border-width: 12px 18px; border-style: solid; border-color: rgb(61, 86, 224); display: inline-block; user-select: auto; box-sizing: border-box; cursor: pointer;" rel="noopener noreferrer" fr-original-style="font-size: 14px; font-family: Helvetica, Arial, sans-serif; color: #ffffff; font-weight: bold; text-decoration: none; border-radius: 5px; background-color: #3D56E0; border-top: 12px solid #3D56E0; border-bottom: 12px solid #3D56E0; border-right: 18px solid #3D56E0; border-left: 18px solid #3D56E0; display: inline-block;">Download full course details here</a></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Closed groups of 6 to 18 learners per session.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Learn how to engage in meaningful conversations about workplace wellbeing with the supports designed to enhance your skills as an effective leader.</p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Empowering leaders and managers to support mental wellbeing in the workplace. This comprehensive course is designed to equip learners with the necessary knowledge and skills to support themselves and their team&rsquo;s wellbeing.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Balancing the individual versus the business needs is a common conundrum many workplaces face when it comes to making suitable adjustments for someone&#39;s mental wellbeing.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">By participating in this course, learners will become skilled in how to navigate these challenges with confidence and professionalism.</p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Initially designed as a one-day course, through collaboration with The University of Cambridge, we extended it to offer a two-day option, to enhance a practical application of the course outcomes.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Day two is dedicated to practising the skills learned on day one, allowing for a hands-on approach and providing the attendees with a higher level of confidence going into their wellbeing conversations.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p>

Download full course details here
Closed groups of 6 to 18 learners per session.
Learn how to engage in meaningful conversations about workplace wellbeing with the supports designed to enhance your skills as an effective leader.
Empowering leaders and managers to support mental wellbeing in the workplace. This comprehensive course is designed to equip learners with the necessary knowledge and skills to support themselves and their team’s wellbeing.
Balancing the individual versus the business needs is a common conundrum many workplaces face when it comes to making suitable adjustments for someone's mental wellbeing.
By participating in this course, learners will become skilled in how to navigate these challenges with confidence and professionalism.
Initially designed as a one-day course, through collaboration with The University of Cambridge, we extended it to offer a two-day option, to enhance a practical application of the course outcomes.
Day two is dedicated to practising the skills learned on day one, allowing for a hands-on approach and providing the attendees with a higher level of confidence going into their wellbeing conversations.



Mindmaps Wellbeing

Mental Health Awareness

Mental Health First Aid

Health & Wellbeing

Leadership Skills

Mental Health

Wellbeing

Mental Health At Work

Manager Training

Approved Mental Health Professional (AMHP)

Mental Health Nurse

Closed groups of 6 to 18 learners per session.

Learn how to engage in meaningful conversations about workplace wellbeing with the supports designed to enhance your skills as an effective leader.

Empowering leaders and managers to support mental wellbeing in the workplace. This comprehensive course is designed to equip learners with the necessary knowledge and skills to support themselves and their team’s wellbeing. 


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