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Are you embarking on the journey of mastering data analytics and visualisation in the UK? The 'Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7' is your beacon. Positioned to illuminate the intricate realm of Power BI, this course offers a comprehensive look into the foundational aspects and the advanced features that make Microsoft's tool a standout. With sections meticulously designed ranging from the fundamentals, like data transformation, to advanced concepts, such as integrating Power BI with Python and storytelling with data, this course ensures learners grasp the complete spectrum. With the rising emphasis on data analytics in today's business world, this course acquaints you with Power BI's prowess. It prepares you for the sought-after Microsoft Power BI certification in the UK. Learning Outcomes Comprehend the fundamental aspects of Power BI, from initiating a project to understanding the user interface. Develop proficiency in advanced data transformation techniques and data model creation. Integrate Python with Power BI and harness the benefits of both for enhanced data analytics. Master the art of 'Storytelling with Data' to deliver impactful presentations and reports. Understand and implement Row-Level Security and harness Power BI Cloud services efficiently. Why choose this Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are 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. Who is this Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 for? Individuals keen on obtaining the Microsoft power bi certification UK. Analysts and data professionals aspiring to enhance their data visualisation skills. Business professionals wanting to leverage Power BI for insightful business decision-making. Tech enthusiasts aiming to amalgamate programming (Python) with data analytics. Those seeking to stay updated with the latest trends in Power BI and its evolving capabilities. Career path Data Analyst: Average Salary £30,000 - £40,000 Annually Business Intelligence Developer: Average Salary £35,000 - £45,000 Annually Power BI Developer: Average Salary £40,000 - £50,000 Annually Data Visualisation Specialist: Average Salary £32,000 - £42,000 Annually Business Intelligence Manager: Average Salary £45,000 - £55,000 Annually Data Strategy Consultant: Average Salary £50,000 - £60,000 Annually Prerequisites This Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This course 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. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Section 01: Introduction Welcome! 00:01:00 What is Power BI? 00:03:00 Download & Installing Power BI Desktop 00:04:00 Getting to know the interface 00:03:00 Mini Project: Transform Data 00:07:00 Mini Project: Visualize Data 00:05:00 Mini Project: Creating a Data Model 00:07:00 Course Outline: What will you learn in this course? 00:05:00 How to learn best with this course? 00:03:00 Section 02: Preparing our Project Creating our initial project file 00:04:00 Working with the attached project files 00:04:00 Section 03: Data Transformation - The Query Editor Exploring the Query Editor 00:06:00 Connecting to our data source 00:07:00 Editing rows 00:08:00 Changing data types 00:08:00 Replacing values 00:03:00 Close & Apply 00:03:00 Connecting to a csv file 00:03:00 Connecting to a web page 00:05:00 Extracting characters 00:06:00 Splitting & merging columns 00:09:00 Creating conditional columns 00:06:00 Creating columns from examples 00:09:00 Merging Queries 00:17:00 Pivoting & Unpivoting 00:06:00 Appending Queries 00:08:00 Practice & Solution: Population table 00:15:00 The Fact-Dimension-Model 00:09:00 Practice: Load the dimension table 00:04:00 Organizing our queries in groups 00:03:00 Entering data manually 00:05:00 Creating an index column 00:03:00 Workflow & more transformations 00:05:00 Module summary 00:05:00 Exercise 1 - Instruction 00:02:00 Exercise Solution 00:11:00 Section 04: Data Transformation - Advanced Advanced Editor - Best practices 00:09:00 Performance: References vs. Duplicating 00:10:00 Performance: Enable / Disable Load & Report Refresh 00:05:00 Group by 00:05:00 Mathematical Operations 00:05:00 Run R Script 00:15:00 Using Parameters to dynamically transform data 00:06:00 M formula language: Basics 00:07:00 M formula language: Values, Lists & Tables 00:14:00 M formula language: Functions 00:13:00 M formula language: More functions & steps 00:05:00 Exercise 2 - Instructions 00:01:00 Exercise 2 - solution 00:05:00 Section 05: Creating a Data Model Understanding the relationship 00:05:00 Create & edit relationships 00:06:00 One-to-many & one-to-one relationship 00:06:00 Many-to-many (m:n) relationship 00:08:00 Cross filter direction 00:06:00 Activate & deactivate relationships 00:06:00 Model summary 00:03:00 Exercise 3 Create Model 00:03:00 Exercise 3 Solution 00:02:00 Section 06: Data Visualization Our first visual 00:08:00 The format tab 00:12:00 Understanding tables 00:10:00 Conditional formatting 00:09:00 The Pie Chart 00:06:00 All about the filter visual 00:13:00 The filter pane for developers 00:09:00 Cross filtering & edit interactions 00:04:00 Syncing slicers across pages 00:07:00 Creating drill downs 00:08:00 Creating drill throughs 00:07:00 The tree map visual 00:07:00 The decomposition tree 00:05:00 Understanding the matrix visual 00:05:00 Editing pages 00:07:00 Buttons & Actions 00:09:00 Bookmarks to customize your report 00:10:00 Analytics and Forecasts with line charts 00:10:00 Working with custom visuals 00:07:00 Get data using R Script & R Script visual 00:08:00 Asking questions - Q&A visual 00:04:00 Wrap up - data visualization 00:08:00 Section 07: Power BI & Python Python in Power BI - Plan of attack 00:03:00 Setting up Python for Power BI 00:03:00 Transforming data using Python 00:11:00 Creating visualizations using Python 00:08:00 Violin plots, pair plots & ridge plots using Python 00:15:00 Machine learning (BayesTextAnalyzer) using Python 00:00:00 Performance & Troubleshooting 00:03:00 Section 08: Storytelling with Data Introduction 00:01:00 Show Empathy & Identify the Requirement 00:03:00 Finding the Most Suitable KPI's 00:02:00 Choose an Effective Visualization 00:04:00 Make Use of Natural Reading Pattern 00:03:00 Tell a Story Using Visual Cues 00:05:00 Avoid Chaos & Group Information 00:02:00 Warp Up - Storytelling with Data 00:02:00 Section 09: DAX - The Essentials Introduction 00:03:00 The project data 00:04:00 Measures vs. Calculated Columns 00:15:00 Automatically creating a date table in DAX 00:08:00 CALENDAR 00:05:00 Creating a complete date table with features 00:04:00 Creating key measure table 00:03:00 Aggregation functions 00:06:00 The different versions of COUNT 00:14:00 SUMX - Row based calculations 00:09:00 Section 10: DAX - The CALCULATE function CALCULATE - The basics 00:11:00 Changing the context with FILTER 00:07:00 ALL 00:08:00 ALL SELECTED 00:03:00 ALL EXCEPT 00:07:00 Section 11: Power BI Service - Power BI Cloud How to go on now? 00:03:00 Power BI Pro vs Premium & Signing up 00:04:00 Exploring the interface 00:04:00 Discovering your workspace 00:03:00 Connecting Power BI Desktop & Cloud 00:04:00 Understanding datasets & reports 00:03:00 Working on reports 00:04:00 Updating reports from Power BI Desktop 00:04:00 Creating and working with workspaces 00:07:00 Installing & using a data gateway 00:13:00 Get Quick Insights 00:03:00 Creating dashboards 00:04:00 Sharing our results through Apps 00:10:00 Power BI Mobile App 00:05:00 Creating the layout for the Mobile App 00:04:00 Wrap up Power BI Cloud 00:07:00 Section 12: Row-Level Security Introduction 00:03:00 Creating a Row-Level Security 00:05:00 Row-Level Security in the Cloud 00:04:00 Row-Level Security & Data Model 00:05:00 Dynamic Row-Level Security 00:07:00 Dynamic Many-to-Many RLS 00:04:00 Hierarchical Row-Level Security 00:13:00 Section 13: More data sources JSON & REST API 00:10:00 Setting up a local MySQL database 00:14:00 Connecting to a MySQL database in Power BI 00:05:00 Connecting to a SQL database (PostgreSQL) 00:05:00 Section 14: Next steps to improve & stay up to date Congratulations & next steps 00:06:00 The End 00:01:00 Resources Resources - Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 00:00:00 Assignment Assignment - Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 04:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Course Overview This course, Self-Help Psychology: Mental Freedom, is designed to guide individuals through the process of achieving mental liberation from negative thought patterns and emotional baggage. It combines psychological principles with personal development strategies to help learners cultivate resilience, confidence, and emotional balance. By engaging with the course, participants will explore various techniques and theories to reclaim their mental freedom and transform their mindset, empowering them to lead more fulfilling lives. The course equips learners with the tools necessary for emotional empowerment, self-awareness, and psychological well-being. Course Description Self-Help Psychology: Mental Freedom offers a comprehensive exploration of psychological concepts that foster emotional release and mental clarity. The course covers a range of topics, including cognitive behavioural techniques, emotional regulation, mindfulness practices, and resilience-building exercises. Learners will gain a deeper understanding of how thoughts and emotions affect mental freedom and how to break free from limiting beliefs and self-sabotage. By the end of the course, participants will have developed a set of strategies to enhance mental wellness, cope effectively with stress, and achieve a mindset that is positive and empowered. Course Modules Module 01: Mental Freedom: From PAIN To POWER Module 02: Understanding the Psychology of Self-Empowerment Module 03: Cognitive Behavioural Techniques for Emotional Clarity Module 04: The Role of Mindfulness in Mental Liberation Module 05: Building Resilience and Overcoming Setbacks Module 06: Reprogramming Your Mindset for Success Module 07: Creating a Long-Term Plan for Mental Wellness (See full curriculum) Who is this course for? Individuals seeking to improve mental clarity and emotional well-being Professionals aiming to enhance their personal development and emotional intelligence Beginners with an interest in psychology and self-help techniques Anyone looking to break free from mental barriers and develop a positive mindset Career Path Life Coach Mental Health Support Worker Personal Development Specialist Wellness Consultant Counsellor HR Professional focusing on employee well-being

Course Overview: The Diploma in Social Work Studies Level 5 provides learners with an in-depth understanding of social work, covering key theories, methods, and practices within the field. Designed to enhance knowledge of both theoretical and practical aspects, this course equips students with the skills to navigate the complexities of social care. Learners will gain a broad understanding of working with vulnerable populations, professional conduct, and various intervention models. Upon completion, students will be well-prepared to contribute to the social work sector, providing essential support to individuals and communities. Course Description: This course explores a range of core topics within social work, including the foundational theories, casework processes, and the diverse contexts in which social work practice occurs. Students will delve into the different models of intervention and the role of social workers within multidisciplinary teams. The programme offers insight into working with adults, understanding the principles of conduct, and the professional responsibilities of a social care worker. Throughout the course, learners will develop critical skills in managing casework and applying relevant theories to real-world situations. The course is structured to provide learners with a comprehensive understanding of social work principles, preparing them for future careers in this essential field. Course Modules: Module 01: An Overview of Social Work Module 02: Social Work Basics Module 03: Theories of Social Work and Sociology Module 04: Casework Process and Teamwork Module 05: Dimensions of Social Work / Models of Intervention Module 06: Practice Contexts and Application Module 07: Working with Adults Module 08: Principles of Conduct and Role as Social Care Worker (See full curriculum) Who is this course for? Individuals seeking to pursue a career in social work Professionals aiming to advance in the social care sector Beginners with an interest in social work and sociology Anyone wanting to understand the role of social workers in society Career Path Social Worker Social Care Practitioner Adult Social Care Worker Community Support Worker Social Care Team Leader

Course Overview: This Carpet Cleaner course provides a comprehensive introduction to carpet cleaning, covering the key techniques and knowledge required for effective cleaning and maintenance. Designed for both beginners and those looking to expand their expertise, this course delves into the science behind carpet care and cleaning methods. Learners will gain a solid understanding of carpet types, stain identification, and cleaning processes, along with restoration techniques. The course is ideal for individuals aiming to enhance their skills and pursue a career in carpet cleaning or maintenance. Upon completion, learners will be equipped with the knowledge to confidently tackle various cleaning challenges and restore carpets to their optimal condition. Course Description: In this detailed course, learners will explore the various aspects of carpet cleaning, starting with an introduction to different carpet types and their specific cleaning requirements. Topics include stain identification, effective cleaning techniques, and the cleaning process step by step. The course also covers essential carpet restoration methods, ensuring learners can offer a complete range of services. The structured approach, supported by theoretical knowledge, provides a solid foundation for individuals wishing to start a career in carpet cleaning or professionals seeking to expand their skill set. By the end of the course, learners will be proficient in identifying and managing common carpet issues, cleaning efficiently, and restoring carpets to their best condition. Course Modules: Module 01: Introduction to Carpet Cleaning Module 02: Understanding Carpets Module 03: Identifying Carpet Stains Module 04: Carpet Cleaning Methods Module 05: Carpet Cleaning Process Module 06: Carpet Restoration (See full curriculum) Who is this course for? Individuals seeking to start a career in carpet cleaning Professionals aiming to expand their skillset in carpet maintenance Beginners with an interest in the carpet cleaning industry Business owners or entrepreneurs looking to offer carpet cleaning services Career Path: Carpet Cleaner Carpet Cleaning Specialist Facilities Maintenance Technician Restoration Technician Residential and Commercial Cleaning Services

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals 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 £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals 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 Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals 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 Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00

Learn how to create stunning face painting designs in our online course. Unleash your creativity and impress at every event!

🍫 Welcome to the sweetest journey of your life with Chocolate Making 101! 🍫 Are you passionate about chocolate? Do you dream of creating delectable treats that delight the senses? If so, then this course is your golden ticket to chocolate-making mastery! 🎟️ Unlock the secrets of chocolate craftsmanship with our comprehensive Chocolate Making 101 course. 🍬 Whether you're a budding chocolatier or a seasoned enthusiast, this course will take you on a tantalizing adventure through the world of chocolate.   🌟 Benefits of Taking Chocolate Making 101: Master the Art: Delve into the fundamentals of chocolate making, from tempering to molding, and discover the techniques used by professionals to create artisanal chocolates. Unleash Your Creativity: Learn how to infuse flavors, experiment with textures, and design exquisite chocolate creations that reflect your unique style and personality. Health Consciousness: Understand the nutritional properties of chocolate and explore healthier alternatives, such as sugar-free and vegan options, without compromising on taste. Impress Your Loved Ones: Surprise friends and family with handmade chocolates that are sure to leave a lasting impression. Whether it's a special occasion or just a sweet gesture, your homemade treats will be cherished by all. Entrepreneurial Opportunities: Turn your passion for chocolate into a profitable venture. Learn about the business side of chocolate making, including sourcing ingredients, marketing strategies, and setting up your own chocolate business.   👩‍🍳 Who is this for? Aspiring Chocolatiers: If you've always dreamed of becoming a chocolatier but don't know where to start, this course is for you. We'll guide you through every step of the chocolate-making process, from bean to bar. Home Bakers: Calling all home bakers! Elevate your baking skills and add a touch of luxury to your desserts with our Chocolate Making 101 course. Impress your friends and family with professional-quality chocolates made right in your own kitchen. Chocolate Enthusiasts: Whether you're a self-proclaimed chocoholic or simply have a passion for all things chocolate, this course will satisfy your cravings and deepen your appreciation for the art of chocolate making.   🚀 Career Path Professional Chocolatier: Embark on a delicious career path as a professional chocolatier. Whether you dream of opening your own chocolate shop or working for a prestigious chocolate brand, the skills you gain in this course will set you on the path to success. Culinary Entrepreneur: Combine your love for chocolate with your entrepreneurial spirit and start your own chocolate business. From selling handmade chocolates at farmers' markets to launching an online chocolate boutique, the possibilities are endless. Chocolate Educator: Share your passion for chocolate with others by becoming a chocolate educator. Teach classes, host workshops, or even write your own chocolate-making cookbook. Inspire others to unleash their creativity and explore the world of chocolate.   Don't miss out on this golden opportunity to indulge in your love for chocolate and take your skills to the next level. Enroll in Chocolate Making 101 today and start your journey towards chocolate-making mastery! 🍫✨   FAQ (Frequently Asked Questions) Q1: What equipment do I need to start making chocolate at home? A: Starting with chocolate making at home requires basic equipment that you might already have in your kitchen. You'll need a double boiler or microwave for melting chocolate, a thermometer for temperature control, molds for shaping chocolate, spatulas for stirring and spreading, and parchment paper for lining trays. Additionally, having a kitchen scale can be helpful for precise measurements. Q2: What ingredients are essential for homemade chocolate? A: The basic ingredients for making chocolate include cocoa powder or cocoa beans, cocoa butter, sweeteners such as sugar or honey, and flavorings like vanilla extract or spices. Depending on the type of chocolate you want to make, you may also need milk powder or dairy alternatives for milk chocolate, and emulsifiers such as lecithin to improve texture and shelf life. Q3: Can I make chocolate without specialized equipment? A: Yes, you can make chocolate at home without specialized equipment, although having some tools can make the process easier and more efficient. For instance, you can temper chocolate by hand using the seeding method, which involves melting chocolate, adding unmelted chocolate to lower the temperature, and then stirring until it reaches the desired consistency. While tempering machines and chocolate melangers can streamline the process, they're not strictly necessary for small-scale chocolate making. Q4: How can I troubleshoot common chocolate making problems? A: Common issues in chocolate making include grainy texture, dull appearance, and improper tempering. Graininess often occurs due to improper melting or cooling techniques, while a dull appearance may result from chocolate being heated too quickly or stored incorrectly. To troubleshoot, ensure your equipment is clean and dry, use high-quality ingredients, and follow temperature guidelines closely. If tempering proves challenging, practice and experimentation can help refine your technique over time. Q5: How do I store homemade chocolate? A: Proper storage is essential for maintaining the quality of homemade chocolate. Store it in a cool, dry place away from direct sunlight and strong odors, ideally at a temperature between 60-70°F (15-21°C). Chocolate should be wrapped tightly to prevent moisture absorption and flavor contamination. When stored correctly, homemade chocolate can last several weeks to months, depending on the ingredients used and the tempering process. Course Curriculum Module 1 Chocolate Making Basics Chocolate Making Basics 00:00 Module 2 Moulds and Packaging Moulds and Packaging 00:00 Module 3 Chocolate For Celebrations Chocolate For Celebrations 00:00 Module 4 Finishing Up Finishing Up 00:00

🌟 Unlock Your Potential with Observational Skills for Careers Course! 🌟 Are you looking to skyrocket your career prospects? Do you want to stand out in a competitive job market? Welcome to the Observational Skills for Careers course, your ultimate ticket to success in today's professional world! 🚀 In an era where attention to detail and keen observation are prized assets, mastering observational skills can truly set you apart. Whether you're a seasoned professional or just starting out, honing these skills can open doors to a world of opportunities. 💼   🔍 Why Observational Skills Matter: Imagine being able to notice subtle nuances in your environment that others miss. From interpreting non-verbal cues in meetings to identifying market trends before they emerge, observational skills are invaluable in virtually every industry. By fine-tuning your ability to observe and interpret, you can enhance your decision-making, problem-solving, and communication abilities. 📊   💡 Benefits of Taking Our Course: 🔹 Develop razor-sharp observation skills: Learn how to pay attention to the details that matter, whether you're in a boardroom or a laboratory. 🔹 Enhance critical thinking: Gain the ability to analyze situations from multiple perspectives and make informed judgments. 🔹 Improve communication: Master the art of conveying your observations effectively, whether through written reports or verbal presentations. 🔹 Boost career prospects: Stand out to employers as someone with a keen eye for detail and a knack for problem-solving. 🔹 Excel in any field: Whether you're in finance, healthcare, education, or any other industry, observational skills are universally valuable.   👩‍💼 Who is this for? This course is designed for professionals at all levels who want to take their careers to the next level. 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Embark on a transformative journey through the intricate landscape of networking with the CompTIA Network+ Certification (N10-007). This course isn't just about mastering the intricacies of network models or delving into the depths of cabling and topology; it's about empowering yourself with the skills and knowledge to navigate the digital highways of the modern era confidently. Picture yourself as the architect, laying down the foundations of robust networks, securing them against digital threats, and troubleshooting with finesse. With CompTIA Network+ +, you're not just learning; you're shaping your future in information technology. In this comprehensive course, you'll traverse through 22 meticulously crafted sections, each unlocking a new facet of comptia networking. From understanding the fundamentals of TCP/IP to exploring the nuances of wireless networking and delving into virtualization and cloud computing, every lesson is a stepping stone towards network mastery. Through immersive learning experiences and hands-on comptia network+ practice tests, you'll absorb theoretical knowledge and hone your practical skills, preparing you for real-world challenges. Learning Outcomes: Master network models and topologies, laying a strong foundation for network architecture. Demonstrate proficiency in TCP/IP fundamentals and routing protocols for effective data transmission. Develop expertise in securing networks against cyber threats, ensuring data integrity and confidentiality. Acquire skills in network troubleshooting and monitoring, enabling swift resolution of issues. Apply wireless networking and cloud computing knowledge to design and implement scalable network solutions. Why buy this CompTIA Network+ Certification (N10-007)? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the CompTIA Network+ Certification (N10-007) 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 £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this CompTIA Network+ Certification (N10-007) for? Aspiring IT professionals seeking to kickstart their careers in networking. Students aiming to enhance their employability with industry-recognized certifications. Career changers looking to transition into the dynamic field of information technology. IT professionals seeking to validate their skills and advance their careers. Anyone passionate about mastering the intricacies of comptia network and carving a niche in the digital landscape. Prerequisites This CompTIA Network+ Certification (N10-007) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This CompTIA Network+ Certification (N10-007) 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 Network Administrator: £20,000 - £45,000 Per Annum Network Engineer: £25,000 - £55,000 Per Annum Systems Administrator: £22,000 - £50,000 Per Annum IT Support Technician: £18,000 - £35,000 Per Annum Cyber Security Analyst: £25,000 - £60,000 Per Annum Cloud Solutions Architect: £30,000 - £80,000 Per Annum Course Curriculum Section 01: Introduction Introduction 00:03:00 Section 02: Network Models What is a Model? 00:02:00 OSI vs. TCP/IP Model 00:07:00 Walking Through OSI and TCP/IP 00:12:00 Meet the Frame 00:06:00 The MAC Address 00:07:00 Broadcast vs. Unicast 00:04:00 Introduction to IP Addressing 00:08:00 Packets and Ports 00:05:00 Section 03: Cabling and Topology Network Topologies 00:10:00 Coaxial Cabling 00:05:00 Twisted Pair Cabling 00:06:00 Cat Ratings 00:06:00 Fiber Optic Cabling 00:09:00 Fire Ratings 00:05:00 Legacy Network Connections 00:07:00 Section 04: Ethernet Basics What is Ethernet? 00:07:00 Ethernet Frames 00:07:00 Early Ethernet 00:08:00 The Daddy of Ethernet, 10BaseT 00:03:00 Terminating Twisted Pair 00:14:00 Hubs vs. Switches 00:13:00 Section 05: Modern Ethernet 100BaseT 00:05:00 Connecting Switches 00:05:00 Gigabit Ethernet and 10-Gigabit Ethernet 00:05:00 Transceivers 00:07:00 Connecting Ethernet Scenarios 00:14:00 Section 06: Installing a Physical Network Introduction to Structured Cabling 00:04:00 Terminating Structured Cabling 00:08:00 Equipment Room 00:07:00 Alternative Distribution Panels 00:04:00 Testing Cable 00:09:00 Troubleshooting Structured Cabling, Part 1 00:05:00 Troubleshooting Structured Cabling, Part 2 00:05:00 Using a Toner and Probe 00:03:00 Wired Connection Scenarios 00:11:00 Section 07: TCP/IP Basics Introduction to IP Addressing and Binary 00:13:00 Introduction to ARP 00:04:00 Classful Addressing 00:10:00 Subnet Masks 00:12:00 Subnetting with CIDR 00:10:00 More CIDR Subnetting Practice 00:10:00 Dynamic and Static IP Addressing 00:18:00 Rogue DHCP Servers 00:07:00 Special IP Addresses 00:07:00 IP Addressing Scenarios 00:15:00 Section 08: Routing Introducing Routers 00:15:00 Understanding Ports 00:05:00 Network Address Translation 00:06:00 Implementing NAT 00:03:00 Forwarding Ports 00:18:00 Tour of a SOHO Router 00:12:00 SOHO vs. Enterprise 00:09:00 Static Routes 00:13:00 Dynamic Routing 00:11:00 RIP 00:04:00 OSPF 00:04:00 BGP 00:06:00 Section 09: TCP/IP Applications TCP and UDP 00:07:00 ICMP and IGMP 00:06:00 Handy Tools 00:07:00 Introduction to Wireshark 00:11:00 Introduction to netstat 00:09:00 Web Servers 00:12:00 FTP 00:12:00 E-mail Servers and Clients 00:09:00 Securing E-mail 00:06:00 Telnet and SSH 00:09:00 Network Time Protocol 00:02:00 Network Service Scenarios 00:10:00 Section 10: Network Naming Understanding DNS 00:12:00 Applying DNS 00:19:00 The Hosts File 00:04:00 Net Command 00:08:00 Windows Name Resolution 00:11:00 Dynamic DNS 00:05:00 DNS Troubleshooting 00:13:00 Section 11: Securing TCP/IP Making TCP/IP Secure 00:04:00 Symmetric Encryption 00:06:00 Asymmetric Encryption 00:03:00 Cryptographic Hashes 00:05:00 Identification 00:12:00 Access Control 00:04:00 AAA 00:05:00 Kerberos/EAP 00:08:00 Single Sign-On 00:10:00 Certificates and Trust 00:14:00 Certificate Error Scenarios 00:08:00 Section 12: Advanced Networking Devices Understanding IP Tunneling 00:06:00 Virtual Private Networks 00:13:00 Introduction to VLANs 00:12:00 InterVLAN Routing 00:03:00 Interfacing with Managed Switches 00:11:00 Switch Port Protection 00:07:00 Port Bonding 00:07:00 Port Mirroring 00:04:00 Quality of Service 00:05:00 IDS vs. IPS 00:04:00 Proxy Servers 00:13:00 Load Balancing 00:09:00 Device Placement Scenarios 00:13:00 Section 13: IPv6 Introduction to IPv6 00:13:00 IPv6 Addressing 00:15:00 IPv6 in Action 00:13:00 IPv4 and IPv6 Tunneling 00:05:00 Section 14: Remote Connectivity Telephony Technologies 00:09:00 Optical Carriers 00:03:00 Packet Switching 00:05:00 Connecting with Dial-up 00:05:00 Digital Subscriber Line (DSL) 00:05:00 Connecting with Cable Modems 00:04:00 Connecting with Satellites 00:03:00 ISDN and BPL 00:04:00 Remote Desktop Connectivity 00:05:00 Advanced Remote Control Systems 00:09:00 Section 15: Wireless Networking Introduction to 802.11 00:12:00 802.11 Standards 00:12:00 Power over Ethernet (PoE) 00:04:00 Antennas 00:09:00 Wireless Security Standards 00:16:00 Implementing Wireless Security 00:07:00 Threats to Your Wireless Network 00:07:00 Retro Threats 00:05:00 Wi-Fi Protected Setup (WPS) 00:05:00 Enterprise Wireless 00:06:00 Installing a Wireless Network 00:15:00 Wireless Scenarios 00:07:00 More Wireless Scenarios 00:09:00 Section 16: Virtualization and Cloud Computing Virtualization Basics 00:07:00 Cloud Ownership 00:03:00 Cloud Implementation 00:12:00 Your First Virtual Machine 00:09:00 NAS and SAN 00:16:00 Platform as a Service (PaaS) 00:09:00 Software as a Service (SaaS) 00:03:00 Infrastructure as a Service (IaaS) 00:10:00 Section 17: Mobile Networking Cellular Technologies 00:05:00 Mobile Connectivity 00:07:00 Deploying Mobile Devices 00:05:00 Mobile Access Control 00:06:00 Section 18: Building a Real-World Network Network Types 00:04:00 Network Design 00:10:00 Power Management 00:06:00 Unified Communications 00:11:00 Network Documentation 00:07:00 Contingency Planning 00:10:00 Predicting Hardware Failure 00:05:00 Backups 00:08:00 Section 19: Managing Risk What is Risk Management? 00:06:00 Security Policies 00:08:00 Change Management 00:07:00 User Training 00:03:00 Standard Business Documentation 00:05:00 Mitigating Network Threats 00:05:00 High Availability 00:05:00 Section 20: Protecting Your Network Denial of Service 00:09:00 Malware 00:10:00 Social Engineering 00:04:00 Access Control 00:08:00 Man-in-the-Middle 00:22:00 Introduction to Firewalls 00:05:00 Firewalls 00:10:00 DMZ 00:06:00 Hardening Devices 00:14:00 Physical Security Controls 00:09:00 Testing Network Security 00:08:00 Network Protection Scenarios 00:14:00 Section 21: Network Monitoring SNMP 00:15:00 Documenting Logs 00:09:00 System Monitoring 00:08:00 SIEM (Security Information and Event Management) 00:07:00 Section 22: Network Troubleshooting Network Troubleshooting Theory 00:05:00