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Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents and interests with our special Electrical Machines for Electrical Engineering Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today's workplaces. The Electrical Machines for Electrical Engineering Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Electrical Machines for Electrical Engineering Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Electrical Machines for Electrical Engineering Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At StudyHub, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from StudyHub, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Electrical Machines for Electrical Engineering? 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 Electrical Machines for Electrical Engineering 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 Electrical Machines for Electrical Engineering 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 Electrical Machines for Electrical Engineering does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Electrical Machines for Electrical Engineering 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 Electrical Machines for Electrical Engineering is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Unit 1: Introduction to Electric Machines Module 1- Introduction to Electric Machines 00:03:00 Module 2- Types of Electric Machines and Principle of Electrical Generation 00:09:00 Unit 2: DC Machines Module 1- Importance and Construction of DC Machines 00:26:00 Module 2- Armature Winding and EMF Equation 00:40:00 Module 3-Solved Example 1 00:05:00 Module 4-Solved Example 2 00:04:00 Module 5-Solved Example 3 00:07:00 Module 6-Solved Example 4 00:06:00 Module 7-Separately Excited DC Machine 00:21:00 Module 8-Shunt and Series DC Machines 00:25:00 Module 9-Solved Example 1 on Separately Excited DC Machine 00:07:00 Module 10-Solved Example 2 on Separately Excited DC Machine 00:07:00 Module 11-Solved Example 3 on Shunt Generator 00:04:00 Module 12-Solved Example 4 on Shunt Generator 00:07:00 Module 13-Solved Example 5 on Series DC Generator 00:06:00 Module 14-Types and Applications of Compound DC Motors 00:07:00 Module 15- Torque-Speed Characteristics and Speed Control of Separately Excited DC Motor 00:33:00 Module 16- Torque-Speed Characteristics of Series DC Motor 00:08:00 Module 17-Solved Example 1 on Speed Control 00:08:00 Module 18-Solved Example 2 on Speed Control 00:06:00 Module 19- Starting of DC Machine 00:14:00 Module 20- Armature Reaction in DC Machines 00:10:00 Module 21-Losses in DC Machines 00:04:00 Unit 3: Construction of Transformers Module 1- What is a Transformer 00:02:00 Module 2- Importance of Transformer 00:04:00 Module 3-Iron Core of Transformer 00:04:00 Module 4- Magnetic Circuit Inside Transformer 00:05:00 Module 5- Windings of Transformer 00:03:00 Module 6- Why are Windings Made of Copper 00:01:00 Module 7- Classification of Windings 00:05:00 Module 8- Insulating Material and Transformer Oil 00:02:00 Module 9- Conservator of Transformer 00:03:00 Module 10- Breather of Transformer 00:04:00 Module 11- Bushings of Transformer 00:04:00 Module 12- Tap Changer of Transformer 00:03:00 Module 13- Cooling Tubes of Transformer 00:01:00 Module 14- Buchholz Relay of Transformer 00:02:00 Module 15- Explosion Vent 00:02:00 Module 16- Methods of Cooling 00:03:00 Module 17-Types of Transformers 00:03:00 Module 18- Power Transformer and Distribution Transformer 00:05:00 Module 19- Single Phase Core Type Transformer 00:04:00 Module 20-Single Phase Shell Type Transformer 00:05:00 Module 21- 3 Phase Core Type 00:02:00 Module 22- 3 Phase Shell Type 00:01:00 Module 23- Comparison between Shell and Core CSA 00:01:00 Module 24- Comparison between Shell and Core Type 00:01:00 Module 25- Notes 00:03:00 Module 26-Video Explaining The Components in 3D and Real Life 00:05:00 Unit 4: Fundamentals of Magnetic Circuits Module 1- Introduction to Magnetic Circuits 00:02:00 Module 2- Induced Emf and Current 00:04:00 Module 3- Ampere Right Hand Rule 00:04:00 Module 4- Magnetic Circuit and Important Definitions 00:06:00 Module 5- Linear and Non Linear Materials 00:03:00 Module 6-Flux Linkage and Reluctance 00:04:00 Module 7- Analogy between Electric and Magnetic Circuits 00:06:00 Module 8- Fringing Effect 00:02:00 Module 9- Example 1 Magnetic Circuits 00:07:00 Module 10- Example 2 00:03:00 Module 11- Example 3 00:06:00 Module 12- Application on Magnetic Circuit - Transformers 00:04:00 Unit 5: Theoretical Part on Transformers Module 1- Introduction to Transformers 00:02:00 Module 2- Construction of Transformer 00:02:00 Module 3-Theory of Operation 00:04:00 Module 4- Ideal Transformer 00:05:00 Module 5-Non Ideal Transformer 00:02:00 Module 6- Effect of Loading on Transformer 00:03:00 Module 7- Transformer Regulation 00:03:00 Module 8- Transformer Losses 00:03:00 Module 9- Transformer Efficiency 00:05:00 Module 10- Transformer Rating 00:02:00 Module 11- Question 1 00:01:00 Module 12- Question 2 00:02:00 Module 13- Question 3 00:01:00 Module 14- Example 1 00:01:00 Module 15- Voltage Relation of Transformer 00:04:00 Module 16- Transformer Exact Equivalent Circuit 00:06:00 Module 17- Concept of Refereeing 00:04:00 Module 18- Approximate Equivalent Circuit 00:02:00 Unit 6: Synchronous Machines Module 1- Construction and Principle of Operation of Synchronous Generator 00:29:00 Module 2- Principle of Operation of Synchronous Motor 00:24:00 Module 3- Equivalent Circuit and Phasor Diagram of Non Salient Synchronous Machine 00:29:00 Module 4-Solved Example 1 on Non Salient Machine 00:05:00 Module 5-Solved Example 2 on Non Salient Machine 00:11:00 Module 6-Solved Example 3 on Non Salient Machine 00:07:00 Module 7- Solved Example 4 on Non Salient Machine 00:04:00 Module 8-Solved Example 5 on Non Salient Machine 00:07:00 Module 9-Solved Example 6 on Non Salient Machine 00:03:00 Module 10- Equivalent Circuit and Phasor Diagram of Salient Synchronous Machine 00:39:00 Module 11-Solved Example 1 on Salient Machine 00:09:00 Module 12- Solved Example 2 on Salient Machine 00:05:00 Module 13-Solved Example 3 on Salient Machine 00:10:00 Module 14- Parallel Operation of Two Generators 00:17:00 Module 15- Synchronization of Machine with Grid 00:10:00 Unit 7: Induction Machines Module 1- Construction and Theory of Operation of Induction Machines 00:27:00 Module 2- Equivalent Circuit and Power Flow in Induction Motor 00:23:00 Module 3- Torque-Speed Characteristics of Induction Motor 00:20:00 Module 4- Solved Example 1 on Induction Motor 00:08:00 Module 5-Solved Example 2 on Induction Motor 00:06:00 Module 6-Solved Example 3 on Induction Motor 00:06:00 Module 7-Solved Example 4 on Induction Motor 00:18:00 Module 8-Solved Example 5 on Induction Motor 00:13:00 Module 9- Methods of Speed Control of Induction Motor 00:27:00 Module 10- Methods of Starting of Induction Motor 00:21:00 Module 11-Solved Example on Motor Starter 00:15:00 Module 12- Principle of Operation of Doubly Fed Induction Generator 00:11:00 Module 13-Self Excited Induction Generator 00:08:00 Assignment Assignment - Electrical Machines for Electrical Engineering 00:00:00

The course 'Deep Learning & Neural Networks Python - Keras' provides a comprehensive introduction to deep learning using the Keras library in Python. It covers topics ranging from basic neural networks to more advanced concepts, such as convolutional neural networks, image augmentation, and performance improvement techniques for various datasets. Learning Outcomes: Understand the fundamental concepts of deep learning and how it differs from traditional machine learning. Gain proficiency in using Keras, a powerful deep learning library, for building and training neural network models. Develop practical skills in creating and optimizing neural network models for different datasets, including image recognition tasks and regression problems. Why buy this Deep Learning & Neural Networks Python - Keras? 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 Deep Learning & Neural Networks Python - Keras 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 Deep Learning & Neural Networks Python - Keras 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 Deep Learning & Neural Networks Python - Keras does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Deep Learning & Neural Networks Python - Keras 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 Deep Learning & Neural Networks Python - Keras is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML or DL for the next AI project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation and Sample Program to Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow library Installation and Sample Program to Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation and Switching Theano and TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps and Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training and Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding the Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - k-fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing the Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding the Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing the Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Layer Tuning for Smaller Network Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning for Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding the Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing the Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement by Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement by Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement by Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save and Load Model as YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load and Predict using the Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load and Predict using the Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load and Predict using the Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load and Predict using the Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction to Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading the Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Multi-Layer Perceptron Model Development MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN using MNIST Large CNN using MNIST 00:09:00 Load and Predict using the MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction to Image Augmentation using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation using Rotation and Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding and Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train and Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load and Predict using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00

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