19941 Introduction To Construction courses

Description: Digital marketing is promoting that makes utilization of electronic gadgets, for example, PCs, cell phones, tablets and game consoles to connect with stakeholders. Digital marketing uses technologies or platforms, for instance, sites, email, applications and social media platforms. Transform your career with the specialized knowledge and skills to plan, implement, measure and evaluate digital marketing strategies, and, how these can add to building and supporting successful and coordinated digital marketing campaigns. By the end of this course, students will gain the skills and in-depth knowledge necessary to become a fruitful and professional digital marketer. Who is the course for? Digital marketers who want to upgrade their knowledge and skills in digital marketing. Digital marketers to advance their career goal in digital marketing. Individuals who want to develop and implement online marketing projects. Start Ups. Students. Marketers. Web designers. Entrepreneurs. Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. 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 you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. PDF certificate's turnaround time is 24 hours and for the hardcopy certificate, it is 3-9 working days. 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 career advancement opportunities; 24/7 student support via email. Career Path: Advanced Digital Marketing Course is a useful qualification to possess, and would be beneficial for the following professionals: Social marketing manager. Digital marketing specialist. Digital marketing executive. Digital marketing officer. Digital marketing analyst. Digital client service. SEO leader. Much more. Advanced Digital Marketing Course - New version Module 01: Fundamentals of Digital Marketing Fundamentals of Digital Marketing 00:45:00 Module 02: Growth Hacking Growth Hacking 00:34:00 Module 03: Customer Journey Customer Journey 00:35:00 Module 04: Content Marketing Content Marketing 00:36:00 Module 05: SEO Search Engine Optimisation 00:40:00 Module 06: E-Mail Marketing E-Mail Marketing 00:45:00 Module 07: Facebook Marketing Facebook Marketing 00:43:00 Module 08: Instagram Marketing Instagram Marketing 00:46:00 Module 09: Twitter Marketing Twitter Marketing 00:37:00 Module 10: Youtube Marketing Youtube Marketing 00:36:00 Module 11: Mobile Marketing Mobile Marketing 00:35:00 Advanced Digital Marketing Course - Old Version Digital Marketing Introduction to Internet Marketing and Reputation Management 00:30:00 How to Optimise Your Site for Every Stage of the Buy Cycle 00:30:00 Build Impression on Your Site 00:30:00 Types of Link Building 01:00:00 Importance of Landing Pages 00:30:00 Difference Between Internet Marketing and Online Customer Service 01:00:00 Concept Of Affiliate Programs 01:30:00 About Of Google Analytics 01:00:00 Online Press Releases 00:15:00 How to Get Traffic from Twitter 00:30:00 Importance of Testing E-Mail Messages 00:15:00 What is Viral Marketing 01:00:00 What is EMail Marketing 00:30:00 Difference Between Images and Video 00:15:00 How to Internet Marketing on Facebook 02:00:00 What is Search Engine Optimization(SEO)? 00:30:00 Understanding Search Results 00:15:00 How to Attract Customer on Your Product? 00:15:00 Time Makes Money 00:30:00 How to Test a Landing Page 00:30:00 Best Web Writing 01:00:00 Ways to Use of Humor in You Internet Marketing 00:15:00 Coupon Codes 00:15:00 When to Pull the Plug 00:15:00 Search Engine Optimization What Is Search Engine Optimization? 01:00:00 Search Engines That Use SEO 01:00:00 Using SEO In Website Text 01:00:00 Using SEO For Google Ads 01:00:00 Using SEO For Article Marketing 01:00:00 Using SEO In Press Releases 00:30:00 Using Longtail Keywords 00:30:00 Using Google To Discover The Best Keywords 00:30:00 SEO For Video Ads 00:30:00 SEO In Photos 00:30:00 Blogging With SEO Marketing 01:00:00 Using A SEO Company 01:00:00 Email Marketing Introduction to Email Marketing 00:30:00 Using Email Marketing Software 00:30:00 Building Email Lists by Quantity 00:30:00 Building Email Lists by Quality 00:30:00 Crafting an Email 01:00:00 Analyzing and Tracking Your Email Marketing Strategy 00:30:00 Facebook Marketing Basics Introduction to Facebook 00:15:00 Why You Should Care 00:15:00 Setting up a Facebook Page 00:30:00 How to Get More Likes for Your Facebook Page 00:30:00 Facebook Advertising 00:30:00 How Much Does Facebook Advertising Cost? 00:30:00 Marketing on Facebook 01:00:00 Create a Content Calendar 00:15:00 Understanding Edge Rank & the Art of Engagement 00:15:00 Twitter Marketing TWITTER FOR BUSINESS 00:15:00 TOP TWITTER TIPS 00:15:00 TWITTER IS 00:15:00 BUSINESS TERMS 00:15:00 WHY USE TWITTER FOR MARKETING 00:15:00 TWITTER MARKETING BASICS 01:00:00 TWITTER METRICS 00:30:00 YOUR BIO 00:15:00 WHEN TO TWEET 00:15:00 BUILDING YOUR COMMUNITY 00:15:00 GENERATING LEADS 00:15:00 REAL-TIME TWITTER MARKETING 00:15:00 ENGAGEMENT 00:15:00 TWETIQUETTE (TWEETING ETIQUETTE) 00:15:00 Instagram Marketing What is Instagram? 00:15:00 Instagram for Business 00:15:00 Instagram & Community 00:15:00 Pinterest Social Marketing Introduction 00:30:00 How to Use Pinterest 01:00:00 How to Win the Hearts of the Target Audience on Pinterest 01:00:00 Understanding Pinterest Etiquette 00:30:00 Marketing Strategies to Build Your Brand and Your Followers 02:00:00 Monetizing Pinterest through Market Hunting 01:00:00 Pinterest Tools to Use in Your Marketing Arsenal 00:15:00 Conclusion 00:15:00 Google Adwords Benefits of online advertising and AdWords 00:30:00 Choosing a campaign type 00:30:00 Measure your results 00:30:00 YouTube Video Marketing Create the Perfect YouTube Marketing Video: 5 Tips To Get it Right 00:30:00 YouTube Video Marketing Tips: Join the Community 01:00:00 Marketing Your Product On YouTube: 10 Reasons Why You Should Do It 00:30:00 YouTube Marketing Tips: Promoting Your Perfect Marketing Video 01:00:00 Unique Things You Can Do with Your YouTube Marketing Video 01:00:00 Using YouTube to Market Your Product: Should You Hire a Professional? 01:00:00 Niche Targeted Playlists: Boost Your YouTube Marketing Video 01:00:00 Promote Your Perfect YouTube Marketing Video For Free: Here's How to Do It 00:30:00 Viral Marketing Tips for Your YouTube Video 01:00:00 Using Viral Content: Creating Your Perfect YouTube Marketing Video 02:00:00 YouTube Marketing Secrets-Promote Your Product or Business! 01:00:00 Use YouTube to Create Unlimited Sales for your Business 01:00:00 Choose Your Niche: An Important Step in Your YouTube Marketing Video 01:00:00 Using Viral Content: Creating Your Perfect YouTube Marketing Video 02:00:00 YouTube Marketing Tactics: Are These Products Helpful or Scams? 01:00:00 Refer A Friend Refer A Friend 00:00:00 Mock Exam Mock Exam- Advanced Digital Marketing Course 00:20:00 Final Exam Final Exam- Advanced Digital Marketing Course 00:20:00 Order Your Certificate and transcript Order Your Certificates and Transcripts 00:00:00

Embark on a captivating journey into the world of artificial intelligence with our course, 'Machine Learning Basics.' This voyage begins with an immersive introduction, setting the stage for an exploration into the intricate and fascinating realm of machine learning. Envision yourself unlocking the mysteries of algorithms and data patterns, essential skills in today's technology-driven landscape. The course offers a comprehensive foray into the core principles of machine learning, starting from the very basics and gradually building to more complex concepts, making it an ideal path for beginners and enthusiasts alike. As you delve deeper, each section unravels a vital component of machine learning. Grasp the essentials of regression analysis, understand the role of predictors, and navigate through the functionalities of Minitab, a key tool in data analysis. Journey through the structured world of regression trees and binary logistic regression, and master the art of classification trees. The course also emphasizes the importance of data cleaning and constructing robust data models, culminating in the achievement of learning success. This course is not just an educational experience; it's a gateway to the future of data science and AI. Learning Outcomes Comprehend the basic principles and applications of machine learning. Develop proficiency in regression analysis and predictor identification. Gain practical skills in Minitab for data analysis. Understand and apply regression and classification trees. Acquire expertise in data cleaning and model creation. Why choose this Machine Learning Basics course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Machine Learning Basics course for? Novices eager to delve into machine learning. Data enthusiasts looking to enhance their analytical skills. Professionals in IT and related fields expanding their expertise. Academics and students in computer science and data studies. Career changers interested in the field of data science and AI. Career path Data Analyst - £30,000 to £55,000 Machine Learning Engineer - £40,000 to £80,000 AI Developer - £35,000 to £75,000 Business Intelligence Analyst - £32,000 to £60,000 Research Scientist (Machine Learning) - £45,000 to £85,000 Software Engineer (AI Specialization) - £38,000 to £70,000 Prerequisites This Machine Learning Basics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Basics was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Introduction Introduction to Supervised Machine Learning 00:06:00 Section 02: Regression Introduction to Regression 00:13:00 Evaluating Regression Models 00:11:00 Conditions for Using Regression Models in ML versus in Classical Statistics 00:21:00 Statistically Significant Predictors 00:09:00 Regression Models Including Categorical Predictors. Additive Effects 00:20:00 Regression Models Including Categorical Predictors. Interaction Effects 00:18:00 Section 03: Predictors Multicollinearity among Predictors and its Consequences 00:21:00 Prediction for New Observation. Confidence Interval and Prediction Interval 00:06:00 Model Building. What if the Regression Equation Contains 'Wrong' Predictors? 00:13:00 Section 04: Minitab Stepwise Regression and its Use for Finding the Optimal Model in Minitab 00:13:00 Regression with Minitab. Example. Auto-mpg: Part 1 00:17:00 Regression with Minitab. Example. Auto-mpg: Part 2 00:18:00 Section 05: Regression Trees The Basic idea of Regression Trees 00:18:00 Regression Trees with Minitab. Example. Bike Sharing: Part1 00:15:00 Regression Trees with Minitab. Example. Bike Sharing: Part 2 00:10:00 Section 06: Binary Logistics Regression Introduction to Binary Logistics Regression 00:23:00 Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC 00:20:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 1 00:16:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 2 00:18:00 Section 07: Classification Trees Introduction to Classification Trees 00:12:00 Node Splitting Methods 1. Splitting by Misclassification Rate 00:20:00 Node Splitting Methods 2. Splitting by Gini Impurity or Entropy 00:11:00 Predicted Class for a Node 00:06:00 The Goodness of the Model - 1. Model Misclassification Cost 00:11:00 The Goodness of the Model - 2 ROC. Gain. Lit Binary Classification 00:15:00 The Goodness of the Model - 3. ROC. Gain. Lit. Multinomial Classification 00:08:00 Predefined Prior Probabilities and Input Misclassification Costs 00:11:00 Building the Tree 00:08:00 Classification Trees with Minitab. Example. Maintenance of Machines: Part 1 00:17:00 Classification Trees with Miitab. Example. Maintenance of Machines: Part 2 00:10:00 Section 08: Data Cleaning Data Cleaning: Part 1 00:16:00 Data Cleaning: Part 2 00:17:00 Creating New Features 00:12:00 Section 09: Data Models Polynomial Regression Models for Quantitative Predictor Variables 00:20:00 Interactions Regression Models for Quantitative Predictor Variables 00:15:00 Qualitative and Quantitative Predictors: Interaction Models 00:28:00 Final Models for Duration and TotalCharge: Without Validation 00:18:00 Underfitting or Overfitting: The 'Just Right Model' 00:18:00 The 'Just Right' Model for Duration 00:16:00 The 'Just Right' Model for Duration: A More Detailed Error Analysis 00:12:00 The 'Just Right' Model for TotalCharge 00:14:00 The 'Just Right' Model for ToralCharge: A More Detailed Error Analysis 00:06:00 Section 10: Learning Success Regression Trees for Duration and TotalCharge 00:18:00 Predicting Learning Success: The Problem Statement 00:07:00 Predicting Learning Success: Binary Logistic Regression Models 00:17:00 Predicting Learning Success: Classification Tree Models 00:09:00

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 Autocad Electrical Design 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 Autocad Electrical Design Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Autocad Electrical Design 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 Autocad Electrical Design 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 Autocad Electrical Design? 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 Autocad Electrical Design 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 Autocad Electrical Design 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 Autocad Electrical Design does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Autocad Electrical Design 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 Autocad Electrical Design is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Unit 1- Introduction to Autocad Module 1- Introduction to Electrical Design Drawing 00:05:00 Module 2- Introduction to Autocad 00:02:00 Module 3- Free Activation for Students 00:05:00 Module 4- Starting Autocad and Changing Background 00:03:00 Module 5- Drawing a Line in Autocad 00:04:00 Module 6- Drawing a Rectangle in Autocad 00:04:00 Module 7- Drawing a Circle in Autocad 00:01:00 Module 8- Drawing a Polygon in Autocad 00:03:00 Module 9- Drawing an Arc in Autocad 00:01:00 Module 10- Drawing a PolyLine in Autocad 00:03:00 Module 11- Multiple Lines Using The Offset feature 00:03:00 Module 12- Adding Text to Autocad 00:04:00 Module 13- Extending Lines in Autocad 00:02:00 Module 14- Selection in Autocad 00:05:00 Module 15- F-shortcuts in Autocad 00:02:00 Module 16- Dimensions in Autocad 00:04:00 Module 17- Multi Spiral Line and MLD in Autocad 00:02:00 Module 18- Block and Explode 00:02:00 Module 19- Move and Scale Commands in Autocad 00:02:00 Module 20- Rotate, Mirror and Fillet Commands in Autocad 00:03:00 Module 21-Area Calculation and Adding Layer in Autocad 00:04:00 Module 22- Saving Your File and Autosave Feature 00:08:00 Module 23- Drawing Fluorescent Symbol Using Autocad 00:07:00 Module 24- Autocad Classic Mode and Workspace 00:03:00 Unit 2- Electrical Design Drawing of Distribution System Module 1- Introduction to Dialux 00:02:00 Module 2- Types of Electrical Drawings 00:03:00 Module 3- Different Lighting Situations 00:05:00 Module 4- Understanding Different Types of Lighting Schemes 00:03:00 Module 5- Properties of Good Lighting Scheme 00:01:00 Module 6- Important Definitions for Lighting 00:09:00 Module 7- Utilisation and Maintenance Factor 00:04:00 Module 8- Important Notes When Designing 00:06:00 Module 9-Steps of Project Design 00:04:00 Module 10- Manual Calculation of Lighting 00:07:00 Module 11- Understanding Catalogs and Photometric Data 00:05:00 Module 12-Dialux Interior Design Task Part 1 00:33:00 Module 13-Dialux Interior Design Task Part 2 00:22:00 Module 14-Dialux Interior Design Task Part 3 00:26:00 Module 15-Wiring of Luminaries and Switches Using Autocad 00:39:00 Module 16-Types of Sockets 00:02:00 Module 17- Adding and Wiring of Sockets 00:40:00 Module 18-Panel Schedule for Lighting and Power Circuits 00:31:00 Module 19-Circuit Breakers and Cable Selection 00:36:00 Module 20-Single Line Diagram for Industrial Area and Riser of The Residential Building 00:23:00 Unit 3- Voltage Drop and Short Circuit Analysis Module 1- Voltage Drop in Low Voltage Distribution System and Manual Calculations 00:21:00 Module 2-Short Circuit in Low Voltage Distribution System and Manual Calculations 00:32:00 Module 3-Voltage Drop and Short Circuit Calculations Using ETAP Easily 00:36:00 Unit 4- Earthing System Module 1- Effect of Current on Human Body 00:09:00 Module 2-Types of Electric Hazards 00:08:00 Module 3-Classification of Earthing Systems 00:24:00 Module 4-Components of Earthing System 00:09:00 Module 5- Design and Resistance of Earthing Electrode 00:12:00 Module 6- Design and Resistance of Earthing Conductor 00:13:00 Module 7- Measurement of Earth Resistance by Megger and Three Point Method 00:03:00 Module 8- Design Earthing or Ground Grid Using ETAP 00:21:00 Unit 5- Generator Sizing Module 1- Sizing of Electrical Generator for Power Engineering 00:52:00

Unlock the power of programming with our Basic C# Coding course, designed for beginners eager to embark on a coding journey. Dive into the world of C#, a versatile programming language that forms the backbone of numerous software applications. From understanding the foundations of C# and the .NET Framework to mastering key concepts like operators, statements, and control flow, this course offers a comprehensive introduction to C# coding. Get hands-on experience with arrays, lists, file structures, and dates, and learn essential debugging techniques to ensure your code runs smoothly. Whether you're looking to kickstart a career in software development or want to enhance your problem-solving skills, this course is the ideal starting point to unravel the art of programming. Learning Outcomes Gain a solid understanding of C# and the .NET Framework. Master C# basics, including operators, statements, and control flow. Explore the use of arrays, lists, and working with file structures. Learn to manipulate dates and effectively debug applications. Be prepared to take your coding skills to the next level with a strong foundation in C#. Why choose this Basic C# Coding course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Basic C# Coding course for? Aspiring programmers and software development enthusiasts. Students and beginners seeking an introduction to C# coding. Professionals looking to enhance their problem-solving and logical thinking skills. Individuals considering a career in software development. Anyone curious about the world of programming and its endless possibilities. Career path Junior Software Developer: £20,000 - £35,000 Software Engineer: £30,000 - £60,000 Web Developer: £25,000 - £45,000 Application Developer: £25,000 - £50,000 Database Administrator: £25,000 - £45,000 Quality Assurance Analyst: £20,000 - £40,000 Prerequisites This Basic C# Coding does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Basic C# Coding was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Introduction Course Introduction 00:02:00 Course Curriculum 00:07:00 How to get Pre-requisites 00:03:00 Getting Started on Windows or Linux 00:01:00 How to ask Great Questions 00:02:00 FAQ's 00:01:00 Section 02: Introduction to C# and .NET Framework Introduction to C# 00:07:00 C# vs .NET 00:04:00 What is CLR? 00:05:00 Architecture of .NET Application 00:09:00 Getting Visual Studio 00:07:00 First C# Hello World Application 00:16:00 Assessment Test 00:01:00 Solution for Assessment Test 00:01:00 05 Interview Questions and Answers 00:04:00 Section 03: C# Basic Introduction 00:03:00 Variables 00:24:00 C# Identifiers 00:08:00 Data Types 00:08:00 Type Casting 00:14:00 User Inputs 00:10:00 Comments 00:03:00 Assessment Test 00:01:00 Solution for Assessment Test 00:02:00 03 Interview Questions and Answers 00:02:00 Summary 00:02:00 Section 04: C# Operators Introduction 00:02:00 Arithmetic Operators 00:09:00 Assignment Operators 00:03:00 Comparison Operators 00:03:00 Logical Operators 00:03:00 Strings 00:10:00 String Properties 00:08:00 Booleans 00:06:00 Assessment Test 00:01:00 Solution for Assessment Test 00:01:00 03 Interview Questions and Answers 00:04:00 Summary 00:02:00 Section 05: C# Statements Introduction 00:02:00 If Conditions and Statements 00:12:00 Switch-Case Statements 00:09:00 Assessment Test 00:01:00 Solution for Assessment Test 00:02:00 03 Interview Questions and Answers 00:04:00 Summary 00:02:00 Section 06: C# Control Flow Statements Introduction 00:02:00 While Loop Statement 00:07:00 Do-While Statement 00:03:00 For Loop Statement 00:07:00 Foreach Statement 00:06:00 Break and Continue 00:03:00 Assessment Test 00:01:00 Solution for Assessment Test 00:01:00 03 Interview Questions and Answers 00:02:00 Summary 00:01:00 Section 07: C# Arrays and Lists Introduction 00:01:00 Arrays 00:13:00 Loop Through Arrays 00:10:00 Lists 00:07:00 Assessment Test 00:01:00 Solution for Assessment Test 00:02:00 03 Interview Questions and Answers 00:02:00 Summary 00:02:00 Section 08: Working with File Structure Introduction 00:01:00 System.IO Namespace 00:03:00 File and File Info 00:11:00 Directory and Directory Info 00:08:00 Getting File Path Information 00:05:00 Assessment Test 00:01:00 Solution for Assessment Test 00:01:00 03 Interview Questions and Answers 00:03:00 Summary 00:03:00 Section 09: Working with Dates Introduction 00:02:00 Datetime 00:10:00 TimeSpan 00:06:00 Assessment Test 00:01:00 Solution for Assessment Test 00:01:00 Summary 00:02:00 Section 10: Debugging Applications Introduction 00:02:00 Debugging Tools in Visual Studio 00:13:00 Call Stack Window 00:04:00 Locals and Autos Windows 00:04:00 Summary 00:02:00 Section 11: What's Next? Bonus Lecture for What Next? 00:02:00 Assignment Assignment - Basic C# Coding 00:00:00

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

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00

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

Delve into the realm of qualitative research with our course on 'Interpretative Phenomenological Analysis (IPA)'. This course offers a comprehensive introduction to IPA, laying the foundation for understanding its theoretical underpinnings. The course then moves onto practical aspects including planning an IPA research study and collecting data. The final modules deal with analysis, writing, and exploring advanced designs and innovative approaches in IPA, leaving learners with a complete understanding of the subject Learning Outcomes Comprehend the fundamental concepts of Interpretative Phenomenological Analysis. Plan and execute an IPA research study. Collect and analyse qualitative data effectively. Write a complete and coherent research report. Understand and apply advanced designs and innovative approaches in IPA. Why choose this Interpretative Phenomenological Analysis (IPA) course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Interpretative Phenomenological Analysis (IPA) course for? Aspiring researchers in the field of psychology. Academics looking to diversify their research methodologies. Postgraduate students undertaking qualitative research. Professionals in healthcare or counselling seeking to understand their clients better. Individuals interested in phenomenology and its applications. Career path Research Analyst: £25,000 - £40,000 Clinical Psychologist: £31,000 - £51,000 Academic Researcher: £30,000 - £50,000 Counsellor: £20,000 - £35,000 Behavioural Analyst: £30,000 - £45,000 Healthcare Consultant: £40,000 - £70,000 Prerequisites This Interpretative Phenomenological Analysis (IPA) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Interpretative Phenomenological Analysis (IPA) was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Module 01: Introduction to Interpretative Phenomenological Analysis (IPA) Introduction to Interpretative Phenomenological Analysis (IPA) 00:13:00 Module 02: IPA and the Theory IPA and the Theory 00:10:00 Module 03: Planning an IPA Research Study Planning an IPA Research Study 00:15:00 Module 04: Collecting Data Collecting Data 00:15:00 Module 05: Analysis Analysis 00:15:00 Module 06: Writing Writing 00:11:00 Module 07: Advanced Designs and Innovative Approaches Advanced Designs and Innovative Approaches 00:15:00

The 'Level 2 Diploma in English Grammar' course provides a comprehensive introduction to English grammar, covering the basics of sentence structure, question formation, punctuation, capitalization, spelling, and common mistakes. Participants will gain a solid understanding of fundamental grammar rules and techniques to improve their English language skills. Learning Outcomes: Acquire a foundational understanding of English grammar and its components. Identify and analyze the basic structure of sentences in English. Understand the rules and techniques for forming questions in English. Master the usage of punctuation and capitalization to enhance writing clarity. Improve spelling skills and avoid common spelling errors in English. Recognize and rectify common grammar mistakes made by English learners. Develop strategies to enhance overall English language proficiency and communication. Apply acquired knowledge to create well-structured sentences and written communication. Why buy this Level 2 Diploma in English Grammar? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Certification After studying the course materials of the Level 2 Diploma in English Grammar 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 course for? This Level 2 Diploma in English Grammar does not require you to have any prior qualifications or experience. You can just enrol and start learning.  Prerequisites This Level 2 Diploma in English Grammar 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 Level 2 Diploma in English Grammar is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Module 1: Introduction to the Course Introduction to the Course 00:13:00 Module 2: The Basics of Grammar Basics of Grammar 00:16:00 Module 3: The Basics of Sentence The Basics of Sentence 00:11:00 Module 4: Structure of Sentence Structure of Sentence 00:19:00 Module 5: Question Question 00:13:00 Module 6: Punctuation & Capitalisation Punctuation & Capitalisation 00:24:00 Module 7: Spelling Spelling 00:27:00 Module 8: Common Mistakes & Ways to Improve Common Mistakes & Ways to Improve 00:21:00

The Investment Banking Operations Professional course provides a comprehensive introduction to investment banking, covering its structure, valuation methods, leveraged buyout (LBO) process, initial public offerings (IPOs), and mergers and acquisitions (M&A). Additionally, the course emphasizes ethical considerations in the investment banking industry. Learning Outcomes: Gain a foundational understanding of the investment banking industry and its key functions. Identify the various structures and sides of investment banking, including roles and responsibilities. Learn different valuation methods used in investment banking to assess the worth of assets and companies. Understand the process and mechanics of leveraged buyouts (LBOs) in investment banking. Explore the procedures and intricacies involved in conducting initial public offerings (IPOs). Study the concepts and strategies related to mergers and acquisitions (M&A) in investment banking. Recognize the importance of ethics in the investment banking profession and its impact on decision-making. Why buy this Investment Banking Operations Professional? 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 Investment Banking Operations Professional 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 Investment Banking Operations Professional does not require you to have any prior qualifications or experience. You can just enrol and start learning.  Prerequisites This Investment Banking Operations Professional 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 Investment Banking Operations Professional is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Module 01: Introduction to Investment Banking Introduction to Investment Banking 00:16:00 Module 02: Structure and Side of Investment Banking Structure and Side of Investment Banking 00:16:00 Module 03: Valuation Methods in Investment Banking Valuation Methods in Investment Banking 00:29:00 Module 04: Leveraged Buyout (LBO) Leveraged Buyout (LBO) 00:21:00 Module 05: Initial Public Offering (IPO) Initial Public Offering (IPO) 00:28:00 Module 06: Merger and Acquisition Merger and Acquisition 00:15:00 Module 07: Ethics in Investment Banking Ethics in Investment Banking 00:13:00 Assignment Assignment - Investment Banking Operations Professional 00:00:00