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Overview Dive into the vibrant world of web design with our comprehensive course: 'Web Design (HTML, CSS, Bootstrap) Complete Course.' Embarking on this learning journey, you'll start from the foundational bricks of web creation: HTML. Grasp the art of tagging, creating headers, adding links and images, and various other core components that shape a webpage. Progressing further, delve deep into CSS, the style mastermind behind every website's appealing look. Enhance your design with intricate details like classes, borders, text styles, and the magic of positioning. The voyage doesn't end here! With Bootstrap, the popular framework that makes web designing a breeze, you'll swiftly create responsive designs, including landing pages and business sites. And, once you've crafted your masterpiece, the final module ensures you're well-equipped to host and showcase your project to the world. Learning Outcomes Web Design (HTML, CSS, Bootstrap) Complete Course Comprehend the foundational principles of HTML and its applications in web design. Implement CSS intricacies to stylise and enhance webpage aesthetics. Master the Bootstrap framework for efficient and responsive web design. Construct diverse web pages, including landing pages, business sites, and portfolios. Acquire the know-how to host and maintain websites seamlessly. Why buy this Web Design (HTML, CSS, Bootstrap) Complete Course? 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 Web Design (HTML, CSS, Bootstrap) Complete Course you will be able to take the MCQ test that will assess your knowledge. 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 Web Design (HTML, CSS, Bootstrap) Complete Course for? Aspiring web designers seeking foundational and advanced knowledge. Business owners aiming to establish a robust online presence. Freelancers wishing to expand their service offerings. Graphic designers keen on integrating web design into their skill set. Students and hobbyists exploring a new digital art medium. Prerequisites This Web Design (HTML, CSS, Bootstrap) Complete 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. Career path Web Designer: £25,000 - £50,000 annually Front-End Developer: £30,000 - £55,000 annually UI/UX Designer: £35,000 - £60,000 annually Web Developer: £28,000 - £52,000 annually Bootstrap Specialist: £32,000 - £56,000 annually Website Administrator: £24,000 - £47,000 annually Course Curriculum Web Design (HTML, CSS, Bootstrap) Complete Course Module: 01 1.1 Intro 00:03:00 1.2 Install the Tools and Get Started 00:05:00 Module: 02 2.1 Intro to HTML 00:01:00 2.2 What is HTML 00:11:00 2.3 Start a New HTML File & Use Tags 00:12:00 2.4 Header Tags 00:05:00 2.5 Edit Text 00:09:00 2.6 Links 00:09:00 2.7 Images 00:10:00 2.8 Lists 00:04:00 2.9 Challenge 00:16:00 2.10 HTML Outro 00:01:00 Module: 03 3.1 CSS Intro 00:04:00 3.2 Add CSS Styles 00:16:00 3.3 Classes and IDs 00:07:00 3.4 Borders 00:06:00 3.5 Sizing 00:04:00 3.6 Padding and Margin 00:07:00 3.7 Text Styles 00:04:00 3.8 DIVs 00:08:00 3.9 Postioning 00:08:00 3.10 Hover 00:03:00 3.11 Easily Center Elements 00:02:00 3.12 Fonts 00:06:00 3.13 Challenge 00:23:00 3.14 CSS Outro 00:01:00 Module: 04 4.1 Intro to Bootstrap 00:02:00 4.2 Install Bootstrap 00:10:00 4.3 Indenting and Containers 00:07:00 4.4 The Grid System 00:16:00 4.5 Images 00:07:00 4.6 Buttons 00:06:00 4.7 Challenge 00:11:00 4.8 Bootstrap Outro 00:01:00 Module: 05 5.1 Landing Page Intro 00:01:00 5.2 Sketch Your Landing Page 00:05:00 5.3 The Top Section 00:16:00 5.4 Polish the Top Section 00:06:00 5.5 Adding Images 00:11:00 5.6 The Main Points Section 00:14:00 5.7 Collecting Emails With an Opt-In Form 00:11:00 5.8 Challenge 00:03:00 5.9 Landing Page Outro 00:02:00 Module: 06 6.1 Business Site Intro 00:01:00 6.2 Sketch Up 00:03:00 6.3 Using Fancy Font Logo 00:07:00 6.4 Carousel Basics 00:10:00 6.5 Carousel Extras 00:09:00 6.6 Text on Images 00:15:00 6.7 Phone Number Icon 00:04:00 6.8 Google Maps 00:13:00 6.9 Font Awesome 00:09:00 6.10 Challenge 00:08:00 6.11 Business Site Outro 00:01:00 Module: 07 7.1 Intro 00:01:00 7.2 Portfolio Sketch 00:08:00 7.3 Jumbotron 00:10:00 7.4 Nav Bar 00:24:00 7.5 Panels 00:11:00 7.6 Challenge 00:13:00 7.7 Portfolio Outre 00:01:00 Module: 08 8.1 Hosting 00:01:00 8.2 Bluehost 00:06:00 8.3 Uploading 00:05:00 8.4 Tips 00:11:00 8.5 Hosting Outro 00:01:00

Overview This comprehensive course on Data Science & Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with Python 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 2 sections • 90 lectures • 10:24:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:08:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:07:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Take This Course £249.00 £14.00 1 year Level 3 Course Certificate Number of Units74 Number of Quizzes0 7 hours, 28 minutes Gift this course Description The Diploma in Adobe XD Design course is designed to teach the all-in-one UX/UI solution - Adobe XD for developing a real-world iPhone app. Adobe XD is a UX/UI solution that helps you to design websites, mobile apps and others. The course covers the essential tools and features of Adobe XD so that you can able to apply the skills in your real-world project. You will learn to apply Paper Prototyping techniques and able to create Interactive Prototype. The course also shows you the procedures of opening sketch, Photoshop and Illustrator files with Adobe XD. Finally, you will learn to collaborate with other developers using Zeplin & Avocode. After completing the course, you will learn to use Adobe XD and create a real world App in Adobe XD by following iOS Design guidelines. Entry Requirement: Beginner Designers UX Designers UI Designers Graphic Designers Web Designers Mobile App Designers Developers or Coders Anyone who wants to design User Interfaces or Websites or Mobile Apps Assessment: At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam, you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of applying for NUS Extra Discount Card; 24/7 student support via email. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Course Curriculum Module: 01 Promo Video 00:03:00 What Is Adobe XD 00:07:00 Download And Install Adobe Xd 00:03:00 Why Adobe XD Is So Awesome - Talkinghead 00:04:00 Updates And Upcoming Features Xd 00:03:00 Adobe XD Interface Welcome Screen 00:03:00 Adobe Xd Top Nav Bar 00:02:00 Adoe Xd Interface Toolbar 00:02:00 Properties Panel Adoe Xd Interface 00:03:00 Xd Mac And Win Differences 00:05:00 First Assignment Simple One 00:08:00 Module: 02 Artboards and grids 00:08:00 Tools in xd 00:05:00 Rectangle tool to create buttons 00:07:00 Background and object blur 00:03:00 Ellipse tool 00:02:00 Basics of pen tool 00:03:00 Pen tool to creat Icons 00:06:00 Line tool 00:01:00 Text-tool 00:03:00 Colors Palettes 00:04:00 Color Gradients in Xd 00:06:00 Coolors.io 00:04:00 Masks in xd 00:06:00 Character styles in Xd 00:05:00 Creating and reusing symbols 00:07:00 Repeat grid 00:09:00 Common Shortcuts 00:06:00 Shortcut keys part2 00:08:00 Nested symbols in xd 00:06:00 Module: 03 S03L01 block-level design 00:12:00 S0302 Sketching First Design Idea-block Level Paper 00:08:00 S0303 First Paper Prototype- Adding Details 00:04:00 S0304 Vertical Horizontal Prototypes T Proto 00:09:00 S0305 Level Of Fidelity and prototypes 00:00:00 S0306 adding details to your block design 00:08:00 S0307 using ui design patterns 00:04:00 S0308 creating signup ios screen EXERCISE 00:14:00 Module: 04 S0401 Design preparations 00:05:00 S0402 Color scheme and insprations 00:05:00 S0403 Solving UX problems of old app 00:04:00 S0404 Welcome Screen design 00:10:00 S0405 designing the login screen 00:14:00 S0406 login-activated 00:12:00 S0407 Signup Screen 00:07:00 S0408 dashboard design part 1 00:12:00 S0409 dashboard design part 2 00:11:00 S0410 Sidebar Navigation 00:09:00 S0411 actitivies screen 00:11:00 S0412 sync screen 00:08:00 S0413 sync status update 00:04:00 S0414 using grids to improve designs further 00:05:00 S0415 refining style guides 00:08:00 S0416 IOS Design guidelines 00:09:00 Module: 05 S0501 fixing tap targets 00:06:00 S0502 prototype login and signup screens 00:10:00 S0503 prototyping dashboards and other screens 00:11:00 S0504 sharing prototype with others 00:04:00 S0505 recording prototype on mac 00:02:00 S0506 design Inspect beta 00:04:00 Module: 06 S0601 why to export in 1x 2x 3x 00:09:00 S0602 Perfect example of 1x 2x 3x 00:03:00 S0603 export artboards to create mockups 00:08:00 S0604 batch export 00:06:00 Module: 07 S0701 Live Preview Your App On Iphone 00:02:00 S0702 Developer handoff with Zeplin 00:13:00 S0703 Developer Handoff using Avocode 00:14:00 S0704 open sketch-psd-illustrato import 00:08:00 Module: 08 XD updtaes april may 2018 00:04:00 1st Exercise Asssignment-1 00:03:00 Second Assignment-1 00:03:00 Third Last Assinment - Google Drive 00:03:00 Resources Resources - Diploma In Adobe XD Design 00:00:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Electrical Engineering - Electrical Machines Complete Training Overview Are you looking to begin your electrical machines career or want to develop more advanced skills in electrical machines? Then this electrical engineering - electrical machines complete online training course will set you up with a solid foundation to become a confident electrical engineer and help you to develop your expertise in electrical machines. This electrical engineering - electrical machines complete online training course is accredited by the CPD UK & IPHM. CPD is globally recognised by employers, professional organisations and academic intuitions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD certified certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Whether you are self-taught and you want to fill in the gaps for better efficiency and productivity, this electrical engineering - electrical machines complete online training course will set you up with a solid foundation to become a confident electrical engineer and develop more advanced skills. Gain the essential skills and knowledge you need to propel your career forward as a electrical engineer. The electrical engineering - electrical machines complete online training course will set you up with the appropriate skills and experience needed for the job and is ideal for both beginners and those currently working as a electrical engineer. This comprehensive electrical engineering - electrical machines complete online training course is the perfect way to kickstart your career in the field of electrical machines. This electrical engineering - electrical machines complete online training course will give you a competitive advantage in your career, making you stand out from all other applicants and employees. If you're interested in working as a electrical engineer or want to learn more skills on electrical machines but unsure of where to start, then this electrical engineering - electrical machines complete online training course will set you up with a solid foundation to become a confident electrical engineer and develop more advanced skills. As one of the leading course providers and most renowned e-learning specialists online, we're dedicated to giving you the best educational experience possible. This electrical engineering - electrical machines complete online training course is crafted by industry expert, to enable you to learn quickly and efficiently, and at your own pace and convenience. Who should take this course? This comprehensive electrical engineering - electrical machines complete online training course is suitable for anyone looking to improve their job prospects or aspiring to accelerate their career in this sector and want to gain in-depth knowledge of electrical machines. Entry Requirements There are no academic entry requirements for this electrical engineering - electrical machines complete online training course, and it is open to students of all academic backgrounds. As long as you are aged seventeen or over and have a basic grasp of English, numeracy and ICT, you will be eligible to enrol. Career path This electrical engineering - electrical machines complete online training course opens a brand new door for you to enter the relevant job market and also provides you with the chance to accumulate in-depth knowledge at the side of needed skills to become flourishing in no time. You will also be able to add your new skills to your CV, enhance your career and become more competitive in your chosen industry. Course Curriculum Course Content Introduction to Electric Machines Types of Electric Machines and Principle of Electricity Generation DC Machines Importance and Construction of DC Machines Armature Winding and EMF Equation Solved Example 1 Solved Example 2 Solved Example 3 Solved Example 4 Shunt and Series DC Machines Solved Example 1 on Separately Excited DC Machine Solved Example 2 on Separately Excited DC Machine Solved Example 3 on Shunt Generator Solved Example 4 on Shunt Generator Solved Example 5 on Series DC Generator Types and Applications of Compound DC Motors Torque-Speed Characteristics and Speed Control of Separately Excited DC Motor Torque-Speed Characteristics of Series DC Motor Solved Example 1 on Speed Control Solved Example 2 on Speed Control Starting of DC Machine Armature Reaction in DC Machines Losses in DC Machines Construction of Transformer Magnetic Circuit Inside Transformer Windings of Transformer Why are Windings Made of Copper Why are Windings Made of Copper Insulating Material and Transformer Oil Conservator of Transformer Breather of Transformer Bushings of Transformer Tap Changer of Transformer Cooling Tubes of Transformer Buchholz Relay of Transformer Explosion Vent Methods of Cooling Types of Transformers Power Transformer and Distribution Transformer Single Phase Core Type Transformer Single Phase Shell Type Transformer Three Phase Core Type Transformer Three Phase Shell Type Transformer Comparison between Shell and Core CSA Comparison between Shell and Core Type Notes Video Explaining The Components in 3D and Real Life Fundamentals of Magnetic Circuits for Electrical Engineering Magnetic Circuit and Important Definitions Linear and Non Linear Materials Flux Linkage and Reluctance Analogy between Electric and Magnetic Circuits Fringing Effect Example 1 Magnetic Circuits Example 2 Example 3 Application on Magnetic Circuit - Transformers Theoretical Part on Transformers Introduction to Transformers Construction of Transformer Theory of Operation Ideal Transformer Non Ideal Transformer Effect of Loading on Transformer Transformer Regulation Transformer Losses Transformer Efficiency Transformer Rating Question 1 Question 2 Question 3 Example 1 Voltage Relation of Transformer Transformer Exact Equivalent Circuit Concept of Refereeing Approximate Equivalent Circuit Synchronous Machines Construction and Principle of Operation of Synchronous Generator rinciple of Operation of Synchronous Motor Equivalent Circuit and Phasor Diagram of Non Salient Synchronous Machine Solved Example 1 on Non Salient Machine Solved Example 2 on Non Salient Machine Solved Example 3 on Non Salient Machine Solved Example 4 on Non Salient Machine lved Example 5 on Non Salient Machine Solved Example 6 on Non Salient Machine Equivalent Circuit and Phasor Diagram of Salient Synchronous Machine Solved Example 1 on Salient Machine Solved Example 2 on Salient Machine Solved Example 3 on Salient Machine Parallel Operation of Two Generators Synchronization of Machine with Grid Induction Machines Construction and Theory of Operation of Induction Machines Equivalent Circuit and Power Flow in Induction Motor Torque-Speed Characteristics of Induction Motor Solved Example 1 on Induction Motor Solved Example 2 on Induction Motor Solved Example 3 on Induction Motor Solved Example 4 on Induction Motor Solved Example 5 on Induction Motor Methods of Speed Control of Induction Motor Methods of Starting of Induction Motor Solved Example on Motor Starter Self Excited Induction Generator Recognised Accreditation CPD Certification Service This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Many organisations look for employees with CPD requirements, which means, that by doing this course, you would be a potential candidate in your respective field. Certificate of Achievement Certificate of Achievement from Lead Academy After successfully passing the MCQ exam you will be eligible to order your certificate of achievement as proof of your new skill. The certificate of achievement is an official credential that confirms that you successfully finished a course with Lead Academy. Certificate can be obtained in PDF version at a cost of £12, and there is an additional fee to obtain a printed copy certificate which is £35.  

Highlights of the Course Course Type: Online Learning Duration: 1 to 2 hours Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about MATLAB Simulink Understand the core competencies and principles of MATLAB Simulink Explore the various areas of MATLAB Simulink Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert MATLAB programmer MATLAB Simulink Training Ultimate Bundle Course Master the skills you need to propel your career forward in MATLAB Simulink. This course will equip you with the essential knowledge and skillset that will make you a confident MATLAB programmer and take your career to the next level. This comprehensive ultimate MATLAB Simulink course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this ultimate MATLAB Simulink course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This comprehensive course will teach you the theory of effective MATLAB Simulink practice and equip you with the essential skills, confidence and competence to assist you in the MATLAB Simulink industry. You'll gain a solid understanding of the core competencies required to drive a successful career in MATLAB Simulink. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for MATLAB programmer or for people who are aspiring to specialise in MATLAB Simulink. Enrol in this ultimate MATLAB Simulink course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive ultimate MATLAB Simulink course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this MATLAB Simulink can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This ultimate MATLAB Simulink course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This ultimate MATLAB Simulink course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This ultimate MATLAB Simulink course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. Course Curriculum Applications on Matrices in MATLAB Solving One Non Linear Equation in MATLAB Using Fzero Function 00:15:00 Example 1 on Solving Multiple Non Linear Equations in MATLAB Using Fsolve 00:14:00 Example 2 on Solving Multiple Non Linear Equations in Matlab Using Fsolve 00:12:00 Application Multi Level Inverter Part 1 00:24:00 Application Multi Level Inverter Part 2 00:04:00 Power Electronics Simulations Using Simulink in MATLAB Introduction to MATLAB Simulations Using Simulink 00:03:00 Half Wave Uncontrolled Rectifier Principle of Operation 00:21:00 Half Wave Controlled Rectifier Principle of Operation 00:04:00 Simulation of Half Wave Controlled Rectifier In MATLAB 00:25:00 Simulation of Bridge Controlled Rectifier in MATLAB 00:16:00 AC Chopper with R Load Principle of Operation 00:14:00 Simulation of AC Chopper with R and RL Loads in MATLAB 00:10:00 Buck Regulator Principle of Operation Part 1 00:16:00 Buck Regulator Principle of Operation Part 2 00:16:00 Simulation of Buck Regulator in MATLAB 00:14:00 Boost Regulator Principle of Operation 00:23:00 Simulation of Boost Regulator in MATLAB 00:12:00 Buck-Boost Regulator Principle of Operation 00:17:00 Simulation of Buck-Boost Regulator in MATLAB 00:09:00 Single Phase Half Bridge Inverter Principle of Operation 00:15:00 Simulation of Single Phase Half Bridge Inverter in MATLAB 00:17:00 Single Phase Bridge Principle of Operation 00:05:00 Simulation of Single Phase Bridge Inverter in MATLAB 00:10:00 Three Phase Inverter Obtaining The Line Voltage 00:14:00 Three Phase Inverter Obtaining The Phase Voltage 00:17:00 Simulation of Three Phase Inverter in MATLAB 00:17:00 Simulation of Charging and Discharging Capacitor Using MATLAB 00:10:00 Solar Energy Simulation Using Simulink in MATLAB and ETAP Simulation of PV Cell In MATLAB and Obtaining V-I Characteristics 00:28:00 Get a Complete Grid-Connected PV System For Free 00:25:00 Simulation of PV System in ETAP 00:24:00 DC Motor Simulation Using Simulink in MATLAB Separately Excited DC Motor Principle of Operation 00:20:00 DC Motor Modelling without Load Using Simulink in MATLAB 00:24:00 DC Motor Modelling with Load Using Simulink in MALTAB 00:23:00 DC Motor Block Simulation Using Power Library in MATLAB 00:16:00 Induction Motor Simulation Using Simulink in MATLAB Construction and Theory of Operation of Induction Machines 00:27:00 Equivalent Circuit and Power Flow in Induction Motor 00:23:00 Torque-Speed Characteristics of Induction Motor 00:19:00 Simulation of Induction Motor or Asynchronous Motor Using Simulink 00:33:00 Synchronous Generator Simulation in Simulink of MATLAB Construction and Principle of Operation of Synchronous Generator 00:33:00 Equivalent Circuit and Phasor Diagram of Non Salient Synchronous Machine 00:29:00 Equivalent Circuit and Phasor Diagram of Salient Synchronous Machine 00:38:00 Simulation of Synchronous Machine Connected to Small Power System 00:37:00 Power System Simulations Importing Data from PSCAD Program for Fault Location Detection to MATLAB Program 00:37:00 PID Controller in MATLAB How to Implement PID Controller in Simulink of MATLAB 00:14:00 Tuning a PID Controller In MATLAB Simulink 00:17:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

Students who complete the PV351 workshop will be able to: Determine use and analyze results from various test tools used during commissioning, performance evaluation, operations and maintenance, and troubleshooting. Define the theory, procedures, and processes behind insulation resistance testing, IV curve tracing, infrared cameras and thermal imaging, performance evaluation, and troubleshooting Demonstrate proper set-up, use, and function of PV test tools including: IV curve tracers, insulation resistance testers, and thermal cameras Evaluate the performance of working systems using correct and complete field procedures Troubleshoot and locate common PV array and system faults using appropriate methodologies and testing tools

Enhance your Excel skills with our comprehensive course covering 50 essential tips and techniques. Perfect for beginners and professionals alike, this course offers CPD accreditation and practical insights to boost your career prospects.

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Module 02: Strategy analysis Module 03: Collaboration Module 04: Requirements analysis and Design definition Module 05: Requirements lifecycle management Module 06: Solution quality Module 07: Stakeholder management Module 08: BA Governance Module 09: Legal notes and Copyright information Course 10: Complete Introduction to Business Data Analysis Level 3 Module 1: Statistics Fundamentals Module 2: Data Analysis Module 3: Probability Module 4: Random Variables and Discrete Distributions Module 5: Continuous Distributions Module 6: Sampling Distributions Module 7: Confidence Interval Module 8: Hypothesis Testing with One Sample Module 9: Hypothesis Testing with Two Samples Module 10: The Chi-Square Distribution Module 11: F Distribution and One-Way ANOVA Module 12: Correlation analysis Module 13: Simple Linear Regression Analysis Course 11: Business Intelligence and Data Mining Masterclass Module 01: What is Business Intelligence? 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Course 12: Research Methods in Business Section 01: Applied Project & Research Methods in Business Section 02: Writing a Purpose / Quantitative and Qualitative Research Approaches Section 03: Mixed Method Research Approaches, Ethical Considerations & Writing Effectively Written Methodology Part 3 !@@ Section 04: Writing Data Collection Tools, Qualitative & Quantitative Data Analysis Section 05: Comparing Findings to Literature and Writing the Final Paper Course 13: Computer Science: Graph Theory Algorithms Module 00: Promo Module 01: Introduction Module 02: Common Problem Module 03: Depth First Search Module 04: Breadth First Search Module 05: Breadth First Search Shortest Path on a Grid And much more... Course 14: Data Protection and Data Security Level 2 GDPR Basics GDPR Explained Lawful Basis for Preparation Rights and Breaches Responsibilities and Obligations CPD 165 CPD hours / points Accredited by CPD Quality Standards Who is this course for? 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Career Path The certification and skills you get from this Data Science & Machine Learning with Python 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 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 00:04:00 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 Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 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 00:06:00 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 - Data Science & Machine Learning with Python 00:00:00

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Curriculum of Electrical Machines for Electrical Engineering: Unit 1: Introduction to Electric Machines Module 1- Introduction to Electric Machines Module 2- Types of Electric Machines and Principle of Electrical Generation Unit 2: DC Machines Module 1- Importance and Construction of DC Machines Module 2- Armature Winding and EMF Equation Module 3-Solved Example 1 Module 4-Solved Example 2 Module 5-Solved Example 3 Module 6-Solved Example 4 Module 7-Separately Excited DC Machine Module 8-Shunt and Series DC Machines Module 9-Solved Example 1 on Separately Excited DC Machine Module 10-Solved Example 2 on Separately Excited DC Machine Module 11-Solved Example 3 on Shunt Generator Module 12-Solved Example 4 on Shunt Generator Module 13-Solved Example 5 on Series DC Generator Module 14-Types and Applications of Compound DC Motors Module 15- Torque-Speed Characteristics and Speed Control of Separately Excited DC Motor Module 16- Torque-Speed Characteristics of Series DC Motor Module 17-Solved Example 1 on Speed Control Module 18-Solved Example 2 on Speed Control Module 19- Starting of DC Machine Module 20- Armature Reaction in DC Machines Module 21-Losses in DC Machines Unit 3: Construction of Transformers Module 1- What is a Transformer Module 2- Importance of Transformer Module 3-Iron Core of Transformer Module 4- Magnetic Circuit Inside Transformer Module 5- Windings of Transformer Module 6- Why are Windings Made of Copper Module 7- Classification of Windings Module 8- Insulating Material and Transformer Oil Module 9- Conservator of Transformer Module 10- Breather of Transformer Module 11- Bushings of Transformer Module 12- Tap Changer of Transformer Module 13- Cooling Tubes of Transformer Module 14- Buchholz Relay of Transformer Module 15- Explosion Vent Module 16- Methods of Cooling Module 17-Types of Transformers Module 18- Power Transformer and Distribution Transformer Module 19- Single Phase Core Type Transformer Module 20-Single Phase Shell Type Transformer Module 21- 3 Phase Core Type Module 22- 3 Phase Shell Type Module 23- Comparison between Shell and Core CSA Module 24- Comparison between Shell and Core Type Module 25- Notes Module 26-Video Explaining The Components in 3D and Real Life Unit 4: Fundamentals of Magnetic Circuits Module 1- Introduction to Magnetic Circuits Module 2- Induced Emf and Current Module 3- Ampere Right Hand Rule Module 4- Magnetic Circuit and Important Definitions Module 5- Linear and Non Linear Materials Module 6-Flux Linkage and Reluctance Module 7- Analogy between Electric and Magnetic Circuits Module 8- Fringing Effect Module 9- Example 1 Magnetic Circuits Module 10- Example 2 Module 11- Example 3 Module 12- Application on Magnetic Circuit - Transformers Unit 5: Theoretical Part on Transformers Module 1- Introduction to Transformers Module 2- Construction of Transformer Module 3-Theory of Operation Module 4- Ideal Transformer Module 5-Non Ideal Transformer Module 6- Effect of Loading on Transformer Module 7- Transformer Regulation Module 8- Transformer Losses Module 9- Transformer Efficiency Module 10- Transformer Rating Module 11- Question 1 Module 12- Question 2 Module 13- Question 3 Module 14- Example 1 Module 15- Voltage Relation of Transformer Module 16- Transformer Exact Equivalent Circuit Module 17- Concept of Refereeing Module 18- Approximate Equivalent Circuit Unit 6: Synchronous Machines Module 1- Construction and Principle of Operation of Synchronous Generator Module 2- Principle of Operation of Synchronous Motor Module 3- Equivalent Circuit and Phasor Diagram of Non Salient Synchronous Machine Module 4-Solved Example 1 on Non Salient Machine Module 5-Solved Example 2 on Non Salient Machine Module 6-Solved Example 3 on Non Salient Machine Module 7- Solved Example 4 on Non Salient Machine Module 8-Solved Example 5 on Non Salient Machine Module 9-Solved Example 6 on Non Salient Machine Module 10- Equivalent Circuit and Phasor Diagram of Salient Synchronous Machine Module 11-Solved Example 1 on Salient Machine Module 12- Solved Example 2 on Salient Machine Module 13-Solved Example 3 on Salient Machine Module 14- Parallel Operation of Two Generators Module 15- Synchronization of Machine with Grid Unit 7: Induction Machines Module 1- Construction and Theory of Operation of Induction Machines Module 2- Equivalent Circuit and Power Flow in Induction Motor Module 3- Torque-Speed Characteristics of Induction Motor Module 4- Solved Example 1 on Induction Motor Module 5-Solved Example 2 on Induction Motor Module 6-Solved Example 3 on Induction Motor Module 7-Solved Example 4 on Induction Motor Module 8-Solved Example 5 on Induction Motor Module 9- Methods of Speed Control of Induction Motor Module 10- Methods of Starting of Induction Motor Module 11-Solved Example on Motor Starter Module 12- Principle of Operation of Doubly Fed Induction Generator Module 13-Self Excited Induction Generator This Electrical Machines for Electrical Engineering course holds a prestigious CPD accreditation, symbolising exceptional quality. 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