940 Data Analysis courses delivered On Demand

This course for absolute beginners provides you with the opportunity to systematically learn core statistical and probability concepts, descriptive statistics, hypothesis testing, regression analysis, analysis of variance (ANOVA), and advanced regression/ML methods such as logistics regressions, polynomial regressions, decision trees, and more.

Embark on a captivating journey into the world of artificial intelligence with our course, 'Machine Learning Basics.' This voyage begins with an immersive introduction, setting the stage for an exploration into the intricate and fascinating realm of machine learning. Envision yourself unlocking the mysteries of algorithms and data patterns, essential skills in today's technology-driven landscape. The course offers a comprehensive foray into the core principles of machine learning, starting from the very basics and gradually building to more complex concepts, making it an ideal path for beginners and enthusiasts alike. As you delve deeper, each section unravels a vital component of machine learning. Grasp the essentials of regression analysis, understand the role of predictors, and navigate through the functionalities of Minitab, a key tool in data analysis. Journey through the structured world of regression trees and binary logistic regression, and master the art of classification trees. The course also emphasizes the importance of data cleaning and constructing robust data models, culminating in the achievement of learning success. This course is not just an educational experience; it's a gateway to the future of data science and AI. Learning Outcomes Comprehend the basic principles and applications of machine learning. Develop proficiency in regression analysis and predictor identification. Gain practical skills in Minitab for data analysis. Understand and apply regression and classification trees. Acquire expertise in data cleaning and model creation. Why choose this Machine Learning Basics 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. Who is this Machine Learning Basics course for? Novices eager to delve into machine learning. Data enthusiasts looking to enhance their analytical skills. Professionals in IT and related fields expanding their expertise. Academics and students in computer science and data studies. Career changers interested in the field of data science and AI. Career path Data Analyst - £30,000 to £55,000 Machine Learning Engineer - £40,000 to £80,000 AI Developer - £35,000 to £75,000 Business Intelligence Analyst - £32,000 to £60,000 Research Scientist (Machine Learning) - £45,000 to £85,000 Software Engineer (AI Specialization) - £38,000 to £70,000 Prerequisites This Machine Learning Basics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Basics 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. Certification After studying the course materials, there will be a written assignment test which you can take 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. Course Curriculum Section 01: Introduction Introduction to Supervised Machine Learning 00:06:00 Section 02: Regression Introduction to Regression 00:13:00 Evaluating Regression Models 00:11:00 Conditions for Using Regression Models in ML versus in Classical Statistics 00:21:00 Statistically Significant Predictors 00:09:00 Regression Models Including Categorical Predictors. Additive Effects 00:20:00 Regression Models Including Categorical Predictors. Interaction Effects 00:18:00 Section 03: Predictors Multicollinearity among Predictors and its Consequences 00:21:00 Prediction for New Observation. Confidence Interval and Prediction Interval 00:06:00 Model Building. What if the Regression Equation Contains 'Wrong' Predictors? 00:13:00 Section 04: Minitab Stepwise Regression and its Use for Finding the Optimal Model in Minitab 00:13:00 Regression with Minitab. Example. Auto-mpg: Part 1 00:17:00 Regression with Minitab. Example. Auto-mpg: Part 2 00:18:00 Section 05: Regression Trees The Basic idea of Regression Trees 00:18:00 Regression Trees with Minitab. Example. Bike Sharing: Part1 00:15:00 Regression Trees with Minitab. Example. Bike Sharing: Part 2 00:10:00 Section 06: Binary Logistics Regression Introduction to Binary Logistics Regression 00:23:00 Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC 00:20:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 1 00:16:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 2 00:18:00 Section 07: Classification Trees Introduction to Classification Trees 00:12:00 Node Splitting Methods 1. Splitting by Misclassification Rate 00:20:00 Node Splitting Methods 2. Splitting by Gini Impurity or Entropy 00:11:00 Predicted Class for a Node 00:06:00 The Goodness of the Model - 1. Model Misclassification Cost 00:11:00 The Goodness of the Model - 2 ROC. Gain. Lit Binary Classification 00:15:00 The Goodness of the Model - 3. ROC. Gain. Lit. Multinomial Classification 00:08:00 Predefined Prior Probabilities and Input Misclassification Costs 00:11:00 Building the Tree 00:08:00 Classification Trees with Minitab. Example. Maintenance of Machines: Part 1 00:17:00 Classification Trees with Miitab. Example. Maintenance of Machines: Part 2 00:10:00 Section 08: Data Cleaning Data Cleaning: Part 1 00:16:00 Data Cleaning: Part 2 00:17:00 Creating New Features 00:12:00 Section 09: Data Models Polynomial Regression Models for Quantitative Predictor Variables 00:20:00 Interactions Regression Models for Quantitative Predictor Variables 00:15:00 Qualitative and Quantitative Predictors: Interaction Models 00:28:00 Final Models for Duration and TotalCharge: Without Validation 00:18:00 Underfitting or Overfitting: The 'Just Right Model' 00:18:00 The 'Just Right' Model for Duration 00:16:00 The 'Just Right' Model for Duration: A More Detailed Error Analysis 00:12:00 The 'Just Right' Model for TotalCharge 00:14:00 The 'Just Right' Model for ToralCharge: A More Detailed Error Analysis 00:06:00 Section 10: Learning Success Regression Trees for Duration and TotalCharge 00:18:00 Predicting Learning Success: The Problem Statement 00:07:00 Predicting Learning Success: Binary Logistic Regression Models 00:17:00 Predicting Learning Success: Classification Tree Models 00:09:00

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Research Paper Writing Course Unleash your inner researcher and embark on this thrilling journey to becoming a proficient research paper writer. Our Research Paper Writing course is a straightforward guidance to help you craft research papers that leave a lasting impact! At the beginning of the Research Paper Writing course, you will gain a deep understanding of the scientific method, learning to formulate and conduct research systematically to enhance the credibility and validity of your work. Besides, you will gain proficiency in legal research. Plus, this course will teach you the art of crafting compelling abstracts. You will also master creating top-notch abstracts using the formula of background, aim, scope, and hypothesis.  Our Research Paper Writing course will show you a visual example of an abstract. As you move through the course, you will gain insight into the timeline of a research paper. Furthermore, in this course, you will become familiar with the research paper's table of contents, including the problem statement, previous literature, your hypothesis, supporting data, data analysis, testing of hypothesis, and conclusion. As you are about to finish the Research Paper Writing course, you will get a clear idea about where to start the reading & writing process of the research paper. At the end of the course, you will learn how to use index cards as a practical tool for organizing thoughts and ideas, facilitating a seamless transition from research notes to a cohesive and well-structured paper. Without any further delay, enrol in the Research Paper Writing course to take your research capability to the next level. Why Choose Teachers Training Some of our website features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Be motivated and hard-working Over the age of 16. Certification CPD Certification from The Teachers Training Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. Fundamental concepts Introduction 00:03:00 What is Research 00:05:00 The Scientific Method 00:09:00 Research and Writing Legal Research 00:23:00 Writing the abstract 00:06:00 Demo: How does an abstract look like 00:12:00 How long should it take?: Planning the timescale 00:03:00 Table of Contents: A working hypothesis 00:08:00 Getting to work Where to start?: Reading or Writing 00:02:00 Parting tip: Index Cards 00:06:00 Writing the paper 00:06:00

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A qualitative research method called Interpretative Phenomenological Analysis explores the diverse range of human experiences. Interpretative phenomenological analysis is a potent approach used by IPA researchers to investigate and comprehend the distinctive viewpoints of individuals. Interpretative phenomenological analysis's central idea is to dissect the complex layers of lived experiences. By carefully navigating through participants' narratives, practitioners of Interpretative Phenomenological Analysis uncover the richness of meaning inherent in their stories. Because it can highlight the intricacies in qualitative data, interpretative phenomenological analysis is highly regarded in both the academic and professional worlds. Take our Interpretative Phenomenological Analysis course to embark on a life-changing adventure. Discover the subtleties of using IPA to gain deep understanding of human experiences. Understand how IPA can influence research techniques and provide information for decision-making. Learn IPA to give yourself a competitive edge in sociology, psychology, and medicine. Enroll today to gain the skills necessary for a prosperous career in qualitative analysis, where your mastery of IPA will help you stand out in the ever-changing field. Learning Outcomes: Understand Interpretative Phenomenological Analysis principles for research planning. Apply Interpretative Phenomenological Analysis theory in research design. Develop skills for Interpretative Phenomenological Analysis data collection. Demonstrate proficiency in Interpretative Phenomenological Analysis data analysis. Master effective communication through IPA writing. Explore advanced Interpretative Phenomenological Analysis research designs. CPD 10 CPD hours / points Accredited by CPD Quality Standards Introduction to Interpretative Phenomenological Analysis (IPA) 13:07 1: Introduction to Interpretative Phenomenological Analysis (IPA) 13:07 IPA and the Theory 09:54 2: IPA and the Theory 09:54 Planning an IPA Research Study 14:46 3: Planning an IPA Research Study 14:46 Collecting Data 14:41 4: Collecting Data 14:41 Analysis 14:36 5: Analysis 14:36 Writing 11:22 6: Writing 11:22 Advanced Designs and Innovative Approaches 15:13 7: Advanced Designs and Innovative Approaches 15:13 Order Your CPD Quality Standard Certificate (Optional) 01:00 8: CPD Certificate (Optional) 01:00 Who is this course for? The Interpretative Phenomenological Analysis course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Interpretative Phenomenological Analysis. It is also great for professionals who are already working in Interpretative Phenomenological Analysis and want to get promoted at work. Requirements To enrol in this Interpretative Phenomenological Analysis course, all you need is a basic understanding of the English Language and an internet connection. Career path Qualitative Researcher/Analyst: £30,000 to £45,000 per year Psychological Researcher/Assistant: £25,000 to £40,000 per year Academic Researcher/Lecturer in Psychology: £40,000 to £60,000 per year Social Science Consultant: £35,000 to £55,000 per year Certificates Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed. CPD Quality Standard Certificate Digital certificate - £7.99

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Embark on an enlightening journey with our Anthropology course. Explore the depths of human societies, uncovering the intricacies of culture, language, economics, and more. Tailored for those fascinated by the diverse tapestry of human existence.

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After successfully completing this Office Skills course, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously it was £10 * 11 = £110) Hard Copy Certificate: Free (For The Title Course) PS The delivery charge inside the UK is £3.99, and the international students have to pay £9.99. CPD 115 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Office Skills course bundle. Requirements This Office Skills course is fully compatible with PC's, Mac's, laptops, tablets and Smartphone devices. Career path Having this various expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Office Skills) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.