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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. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum 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 00:01:00 R and RStudio Engine and Coding Environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A Quick Tour 00:04:00 Introduction to Basics Arithmetic With R 00:03:00 Variable Assignment 00:04:00 Basic data types in R 00:03:00 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 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 Factors What is Factor 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Data Frames What's a Data Frame 00:03:00 Creating a Data Frame 00:04:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Lists Why Would You Need Lists 00:01:00 Creating Lists 00:03:00 Selecting Elements From a List 00:03:00 Adding more data to the list 00:02:00 Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 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 Conditional Statements The IF Statement 00:04:00 IF…ELSE 00:03:00 The ELSEIF Statement 00:05:00 Full Exercise 00:03:00 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 00:03:00 For Loop With Conditionals 00:01:00 Using Next and Break With For Loop 00:03:00 Functions What is 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 R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different Ways To Load a Package 00:02:00 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 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 Useful Functions Mathematical Functions 00:05:00 Data Utilities 00:08:00 Regular Expressions Grepl & Grep 00:04:00 Metacharacters 00:05:00 Sub & Gsub 00:02:00 More Metacharacters 00:04:00 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 Getting and Cleaning Data Get and Set Current Directory 00:04:00 Get Data From the Web 00:04:00 Loading Flat Files 00:05:00 Loading Excel files 00:03:00 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 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 Ccomponent: 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 Supplementary Resources Supplementary Resources - Learning R Programming for Data Science 00:00:00 Certificate of Achievement Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

MATLAB Simulink Course Overview Are you looking to begin your MATLAB Simulink career or want to develop more advanced skills in MATLAB Simulink? Then this complete MATLAB Simulink course bundle - online training course will set you up with a solid foundation to become a confident MATLAB programmer and help you to develop your expertise in MATLAB Simulink. This complete MATLAB Simulink course bundle - 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 complete MATLAB Simulink course bundle - online training course will set you up with a solid foundation to become a confident MATLAB programmer and develop more advanced skills. Gain the essential skills and knowledge you need to propel your career forward as a MATLAB programmer. The complete MATLAB Simulink course bundle - 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 MATLAB programmer. This comprehensive complete MATLAB Simulink course bundle - online training course is the perfect way to kickstart your career in the field of MATLAB Simulink. This complete MATLAB Simulink course bundle - 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 MATLAB programmer or want to learn more skills on MATLAB Simulink but unsure of where to start, then this complete MATLAB Simulink course bundle - online training course will set you up with a solid foundation to become a confident MATLAB programmer 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 complete MATLAB Simulink course bundle - 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 complete MATLAB Simulink course bundle - 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 MATLAB Simulink. Entry Requirements There are no academic entry requirements for this complete MATLAB Simulink course bundle - 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 complete MATLAB Simulink course bundle - 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 Applications on Matrices in MATLAB Solving One Non Linear Equation in MATLAB Using Fzero Function Example 1 on Solving Multiple Non Linear Equations in MATLAB Using Fsolve Function Example 2 on Solving Multiple Non Linear Equations in Matlab Using Fsolve Application Multi Level Inverter Part 1 Application Multi Level Inverter Part 2 Power Electronics Simulations Using Simulink in MATLAB Introduction to MATLAB Simulations Using Simulink Half Wave Uncontrolled Rectifier Principle of Operation Half Wave Controlled Rectifier Principle of Operation Simulation of Half Wave Controlled Rectifier Using Simulink In Matlab Simulation of Bridge Controlled Rectifier in Matlab AC Chopper with R Load Principle of Operation Simulation of AC Chopper with R and RL Loads in MATLAB Buck Regulator Principle of Operation Part 1 Buck Regulator Principle of Operation Part 2 Simulation of Buck Regulator in MATLAB Boost Regulator Principle of Operation Simulation of Boost Regulator in MATLAB Buck-Boost Regulator Principle of Operation Simulation of Buck-Boost Regulator in MATLAB Single Phase Half Bridge Inverter Principle of Operation Simulation of Single Phase Half Bridge Inverter in MATLAB Single Phase Half Bridge Inverter Principle of Operation Simulation of Single Phase Half Bridge Inverter in MATLAB Three Phase Inverter Obtaining The Line Voltage Three Phase Inverters and Obtaining The Phase Voltages Simulation of Three Phase Inverter Simulation of Charging and Discharging Capacitor Using Matlab Solar Energy Simulation Using Simulink in MATLAB and ETAP Simulation of PV Cell in MATLAB and Obtaining V-I Characteristics DC Motor Simulation Using Simulink in MATLAB Separately Excited DC Motor Principle of Operation DC Motor Modelling without Load Using Simulink in MATLAB DC Motor Modelling with Load Using Simulink in MALTAB DC Motor Block Simulation Using Power Library in MATLAB Induction Motor Simulation Using Simulink in MATLAB Construction and Theory of Operation of Induction Machines Equivalent Circuit and Power Flow in Induction Motor Torque-Speed Characteristics of Induction Motor Simulation of Induction Motor or Asynchronous Motor Using Simulink Synchronous Generator Simulation in Simulink of MATLAB Construction and Principle of Operation of Synchronous Generator Equivalent Circuit and Phasor Diagram of Non Salient Synchronous Machine Equivalent Circuit and Phasor Diagram of Salient Synchronous Machine Simulation of Synchronous Machine Connected to Small Power System Power System Simulations Importing Data from PSCAD Program for Fault Location Detection to MATLAB Program PID Controller in MATLAB How to Implement PID Controller in Simulink of MATLAB Tuning a PID Controller in MATLAB Simulink 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.   FAQs Is CPD a recognised qualification in the UK? 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. Are QLS courses recognised? Although QLS courses are not subject to Ofqual regulation, they must adhere to an extremely high level that is set and regulated independently across the globe. A course that has been approved by the Quality Licence Scheme simply indicates that it has been examined and evaluated in terms of quality and fulfils the predetermined quality standards. When will I receive my certificate? For CPD accredited PDF certificate it will take 24 hours, however for the hardcopy CPD certificate takes 5-7 business days and for the Quality License Scheme certificate it will take 7-9 business days. Can I pay by invoice? Yes, you can pay via Invoice or Purchase Order, please contact us at info@lead-academy.org for invoice payment. Can I pay via instalment? Yes, you can pay via instalments at checkout. How to take online classes from home? Our platform provides easy and comfortable access for all learners; all you need is a stable internet connection and a device such as a laptop, desktop PC, tablet, or mobile phone. The learning site is accessible 24/7, allowing you to take the course at your own pace while relaxing in the privacy of your home or workplace. Does age matter in online learning? No, there is no age limit for online learning. Online learning is accessible to people of all ages and requires no age-specific criteria to pursue a course of interest. As opposed to degrees pursued at university, online courses are designed to break the barriers of age limitation that aim to limit the learner's ability to learn new things, diversify their skills, and expand their horizons. When I will get the login details for my course? After successfully purchasing the course, you will receive an email within 24 hours with the login details of your course. Kindly check your inbox, junk or spam folder, or you can contact our client success team via info@lead-academy.org

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

Course Overview Peek into the world of data science and machine learning with the comprehensive Data Science & Machine Learning With R in 2021 course. This course will provide you with a detailed understanding of both machine learning and data science. In addition, you will acquire essential skills to pursue a career in this growing industry. The Data Science & Machine Learning With R in 2021 course will teach you the core concept of data science. You will be able to recognize different data types and structures. From the modules, you will receive an introduction to the intermediate R Section. The course will show you the techniques of data manipulation in R. You will know the process of data visualization with R and learn to create reports with R markdown. The Data Science & Machine Learning With R in 2021 course will provide you with an insight into the fundamentals of machine learning. You will understand the principles of data processing, linear regression, logistic regression and more.  This highly informative Data Science & Machine Learning With R in 2021 course will equip you with the essential skills of data science. If you desire to become a professional data scientist, this course can be your stepping stone. So, enroll in the course and fast track your career. Learning Outcomes Learn the definition of data science Understand the basics of machine learning Enrich your knowledge of data types and structures Know the process of data manipulation in R Gain the ability to create reports with R markdown Become skilled in building web apps with R shiny Who is this course for? Aspiring data scientists or individuals interested in learning data science and machine learning  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. Certification After you have successfully completed the course, 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 hardcopy at the cost of £39 or in PDF format at the 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  The Data Science & Machine Learning With R in 2021 course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Data Scientist Data Science and Machine Learning Course Intro Data Science and Machine Learning Introduction 00:03:00 What is Data Science 00:10:00 Machine Learning Overview 00:05:00 Who is This Course for 00:03:00 Data Science and Machine Learning Marketplace 00:05:00 Data Science and Machine Learning Job Opportunities 00:03:00 Data Types and Structures in R Getting Started 00:16:00 Basics 00:06:00 Files 00:11:00 RStudio 00:07:00 Tidyverse 00:05:00 Resources 00:04:00 Data Types and Structures in R Unit Introduction 00:30:00 Basic Type 00:09:00 Vector Part One 00:20:00 Vectors Part Two 00:25:00 Vectors - Missing Values 00:16:00 Vectors - Coercion 00:14:00 Vectors - Naming 00:10:00 Vectors - Misc 00:06:00 Creating Matrics 00:31:00 List 00:32:00 Introduction to Data Frames 00:19:00 Creating Data Frames 00:20:00 Data Frames: Helper Functions 00:31:00 Data Frames Tibbles 00:39:00 Intermediate R Intermediate Introduction 00:47:00 Relational Operations 00:11:00 Conditional Statements 00:11:00 Loops 00:08:00 Functions 00:14:00 Packages 00:11:00 Factors 00:28:00 Dates and Times 00:30:00 Functional Programming 00:37:00 Data Import or Export 00:22:00 Database1 00:27:00 Data Manipulation in R Data Manipulation in R Introduction 00:36:00 Tidy Data 00:11:00 The Pipe Operator 00:15:00 The Filter Verb 00:22:00 The Select Verb 00:46:00 The Mutate Verb 00:32:00 The Arrange Verb 00:10:00 The Summarize Verb 00:23:00 Data Pivoting 00:43:00 JSON Parsing 00:11:00 String Manipulation 00:33:00 Web Scraping 00:59:00 Data Visualization in R Data Visualization in R Section Intro 00:17:00 Getting Started 00:16:00 Aesthetics Mappings 00:25:00 Single Variable Plots 00:37:00 Two Variable Plots 00:21:00 Facets, Layering, and Coordinate Systems 00:18:00 Styling and Saving 00:12:00 Creating Reports with R Markdown Creating with R Markdown 00:29:00 Building Webapps with R Shiny Introduction to R Shiny 00:26:00 A Basic R Shiny App 00:31:00 Other Examples with R Shiny 00:34:00 Introduction to Machine Learning Machine Learning Part 1 00:22:00 Machine Learning Part 2 00:47:00 Starting A Career in Data Science Starting a Data Science Career Section Overview 00:03:00 Data Science Resume 00:04:00 Getting Started with Freelancing 00:05:00 Top Freelance Websites 00:05:00 Personal Branding 00:05:00 Importance of Website and Blo 00:04:00 Networking Do's and Don'ts 00:04:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Overview This comprehensive course on R Programming for Data Science will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This R Programming for Data Science 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 R Programming for Data Science. It is available to all students, of all academic backgrounds. Requirements Our R Programming for Data Science 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 23 sections • 129 lectures • 06:25:00 total length •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?: 00:01:00 •Engine and coding environment: 00:03:00 •Installing R and RStudio: 00:04:00 •RStudio: A quick tour: 00:04:00 •Arithmetic with R: 00:03:00 •Variable assignment: 00:04:00 •Basic data types in R: 00:03:00 •Creating a vector: 00:05:00 •Naming a vector: 00:04:00 •Vector selection: 00:06:00 •Selection by comparison: 00:04:00 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •Mathematical functions: 00:05:00 •Data Utilities: 00:08:00 •Additional Materials: 00:00:00 •grepl & grep: 00:04:00 •Metacharacters: 00:05:00 •sub & gsub: 00:02:00 •More metacharacters: 00:04:00 •Additional Materials: 00:00:00 •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 •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 •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 •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 - R Programming for Data Science: 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 'Mathematics' course provides a comprehensive study of various mathematical concepts, including mathematical logic, matrices, trigonometric functions, pair of straight lines, lines & planes, and linear programming. It aims to enhance students' mathematical knowledge and problem-solving skills. Learning Outcomes: Understand the fundamentals of mathematical logic and its application in problem-solving. Comprehend matrix operations and solve mathematical problems involving matrices. Analyze trigonometric functions and their properties in various mathematical contexts. Solve problems related to pair of straight lines and their equations. Explore lines and planes in three-dimensional space and their geometric properties. Apply linear programming techniques to optimize solutions in real-world scenarios. Acquire a strong foundation in mathematics and develop critical thinking abilities. Demonstrate proficiency in mathematical concepts through problem-solving exercises. Utilize mathematical tools and techniques in practical applications and academic settings. Successfully complete the Mathematics course with a comprehensive understanding of key mathematical principles. Why buy this Mathematics? 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 Mathematics 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 Mathematics 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 Mathematics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Mathematics 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 Mathematics is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Unit 01: Introduction Introduction 00:01:00 Unit 02: Mathematical Logic Introduction to Mathematical Logic, What is Sentence, Statements and their Types 00:02:00 Introduction to Logical Connectivity, Tautology, Contradiction, Contingency, Pattern 00:06:00 Quantitative and Quantified Statement and types and example 00:03:00 Dual: Replacing of Connections and Symbols 00:02:00 Negations of Compound Statement, Converse, Inverse, & Contrapositive 00:03:00 Algebra of Statements and Law 00:05:00 Real Life application of Logic to Switching Electric Circuit 00:05:00 Unit 03: Matrices Introduction to Matrices, Multiplication and Addition using Matrix 00:06:00 Inverse of Matrix Uniqueness of Inverse, Elementary Transformation 00:09:00 Method of REDUCTION AND INVERSION with real life example how we can implement 00:17:00 Unit 04: Trigonometric Functions Introduction to Trigonometric Function 00:03:00 General Solutions and Theorem 00:10:00 Solution of Triangle: Polar Co-ordinates 00:22:00 Rules and Theorems of Sin Cosine and Tan 00:22:00 Unit 05: Pair of Straight Line Introduction & Combined Equations 00:07:00 Degrees and Types 00:13:00 Some Theorem 00:17:00 Unit 06: Lines & Planes Introduction - vector Cartesian theorem 00:02:00 Cartesian Equation & 2 Point Theorem 00:03:00 Theorems & Problem Solving 00:05:00 Distance of Point Line 00:05:00 Skew Lines 00:01:00 Distance of skew lines 00:03:00 Distance between parallel lines 00:02:00 Equation of Plane and Cartesian Form 00:10:00 Unit 07: Linear Programming Linear Programming Introduction 00:08:00 Introduction to LPP (Linear Programming Problem) 00:05:00 LPP Problem Solving 00:07:00 Assignment Assignment - Mathematics 00:00:00

Overview This comprehensive course on Advanced Mathematics will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Advanced Mathematics 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 Advanced Mathematics. It is available to all students, of all academic backgrounds. Requirements Our Advanced Mathematics 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 8 sections • 30 lectures • 03:23:00 total length •Introduction: 00:01:00 •Introduction to Mathematical Logic, What is Sentence, Statements and their Types: 00:02:00 •Introduction to Logical Connectivity, Tautology, Contradiction, Contingency, Pattern: 00:06:00 •Quantitative and Quantified Statement and types and example: 00:03:00 •Dual: Replacing of Connections and Symbols: 00:02:00 •Negations of Compound Statement, Converse, Inverse, & Contrapositive: 00:03:00 •Algebra of Statements and Law: 00:05:00 •Real Life application of Logic to Switching Electric Circuit: 00:05:00 •Introduction to Matrices, Multiplication and Addition using Matrix: 00:06:00 •Inverse of Matrix Uniqueness of Inverse, Elementary Transformation: 00:09:00 •Method of REDUCTION AND INVERSION with real life example how we can implement: 00:17:00 •Introduction to Trigonometric Function: 00:03:00 •General Solutions and Theorem: 00:10:00 •Solution of Triangle: Polar Co-ordinates: 00:21:00 •Rules and Theorems of Sin Cosine and Tan: 00:22:00 •Introduction & Combined Equations: 00:07:00 •Degrees and Types: 00:13:00 •Some Theorem: 00:17:00 •Introduction - vector Cartesian theorem: 00:02:00 •Cartesian Equation & 2 Point Theorem: 00:03:00 •Theorems & Problem Solving: 00:05:00 •Distance of Point Line: 00:05:00 •Skew Lines: 00:01:00 •Distance of skew lines: 00:03:00 •Distance between parallel lines: 00:02:00 •Equation of Plane and Cartesian Form: 00:10:00 •Linear Programming Introduction: 00:08:00 •Introduction to LPP (Linear Programming Problem): 00:05:00 •LPP Problem Solving: 00:07:00 •Assignment - Advanced Mathematics: 00:00:00

Overview This comprehensive course on Data Science & Machine Learning with R 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 R comes with accredited certification, 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 R. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with R 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 10 sections • 69 lectures • 22:07:00 total length •Data Science and Machine Learning Introduction: 00:03:00 •What is Data Science: 00:10:00 •Machine Learning Overview: 00:05:00 •Who is This Course for: 00:03:00 •Data Science and Machine Learning Marketplace: 00:05:00 •Data Science and Machine Learning Job Opportunities: 00:03:00 •Getting Started: 00:11:00 •Basics: 00:06:00 •Files: 00:11:00 •RStudio: 00:07:00 •Tidyverse: 00:05:00 •Resources: 00:04:00 •Unit Introduction: 00:30:00 •Basic Type: 00:09:00 •Vector Part One: 00:20:00 •Vectors Part Two: 00:25:00 •Vectors - Missing Values: 00:16:00 •Vectors - Coercion: 00:14:00 •Vectors - Naming: 00:10:00 •Vectors - Misc: 00:06:00 •Creating Matrics: 00:31:00 •List: 00:32:00 •Introduction to Data Frames: 00:19:00 •Creating Data Frames: 00:20:00 •Data Frames: Helper Functions: 00:31:00 •Data Frames Tibbles: 00:39:00 •Intermediate Introduction: 00:47:00 •Relational Operations: 00:11:00 •Conditional Statements: 00:11:00 •Loops: 00:08:00 •Functions: 00:14:00 •Packages: 00:11:00 •Factors: 00:28:00 •Dates and Times: 00:30:00 •Functional Programming: 00:37:00 •Data Import or Export: 00:22:00 •Database: 00:27:00 •Data Manipulation in R Introduction: 00:36:00 •Tidy Data: 00:11:00 •The Pipe Operator: 00:15:00 •The Filter Verb: 00:22:00 •The Select Verb: 00:46:00 •The Mutate Verb: 00:32:00 •The Arrange Verb: 00:10:00 •The Summarize Verb: 00:23:00 •Data Pivoting: 00:43:00 •JSON Parsing: 00:11:00 •String Manipulation: 00:33:00 •Web Scraping: 00:59:00 •Data Visualization in R Section Intro: 00:17:00 •Getting Started: 00:16:00 •Aesthetics Mappings: 00:25:00 •Single Variable Plots: 00:37:00 •Two Variable Plots: 00:21:00 •Facets, Layering, and Coordinate Systems: 00:18:00 •Styling and Saving: 00:12:00 •Creating with R Markdown: 00:29:00 •Introduction to R Shiny: 00:26:00 •A Basic R Shiny App: 00:31:00 •Other Examples with R Shiny: 00:34:00 •Machine Learning Part 1: 00:22:00 •Machine Learning Part 2: 00:47:00 •Starting a Data Science Career Section Overview: 00:03:00 •Data Science Resume: 00:04:00 •Getting Started with Freelancing: 00:05:00 •Top Freelance Websites: 00:05:00 •Personal Branding: 00:05:00 •Importance of Website and Blo: 00:04:00 •Networking Do's and Don'ts: 00:04:00

The 'MATLAB Simulink for Electrical Power Engineering' course focuses on practical applications and simulations using MATLAB and Simulink for power electronics, solar energy, DC motors, synchronous generators, and induction motors. It aims to provide participants with hands-on experience in electrical power engineering simulations and analysis using MATLAB and Simulink. Learning Outcomes: Understand the applications of matrices in MATLAB and solve non-linear equations using appropriate functions. Simulate power electronics circuits, including rectifiers, choppers, regulators, and inverters, using Simulink in MATLAB. Analyze and simulate solar energy systems and separately excited DC machines in MATLAB. Model and simulate synchronous generators connected to a small power system using MATLAB and Simulink. Simulate induction motors and study their equivalent circuits and torque-speed characteristics using Simulink. Implement PID controllers in Simulink and tune them for effective control in power systems simulations. Acquire hands-on skills in using MATLAB and Simulink to perform various electrical power engineering simulations. Apply MATLAB and Simulink tools to solve practical electrical power engineering problems. Develop an in-depth understanding of power electronics, motor simulations, and solar energy systems. Successfully complete the course with the ability to perform advanced electrical power engineering simulations using MATLAB and Simulink. Why buy this MATLAB Simulink for Electrical Power 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 MATLAB Simulink for Electrical Power 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 MATLAB Simulink for Electrical Power 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 MATLAB Simulink for Electrical Power Engineering does not require you to have any prior qualifications or experience. You can just enrol and start learning.This MATLAB Simulink for Electrical Power 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 MATLAB Simulink for Electrical Power Engineering is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Unit 1- Applications on Matrices in MATLAB Module 1- Solving One Non Linear Equation in MATLAB Using Fzero Function 00:15:00 Module 2-Example 1 on Solving Multiple Non Linear Equations in MATLAB Using Fsolve Function 00:15:00 Module 3- Example 2 on Solving Multiple Non Linear Equations in Matlab Using Fsolve 00:13:00 Module 4-Application Multi Level Inverter Part 1 00:25:00 Module 5- Application Multi Level Inverter Part 2 00:05:00 Unit 2-Power Electronics Simulations Using Simulink in MATLAB Module 1-Introduction to MATLAB Simulations Using Simulink 00:04:00 Module 2-Half Wave Uncontrolled Rectifier with R Load Principle of Operation 00:21:00 Module 3- Half Wave Controlled Rectifier R Load Principle of Operation 00:05:00 Module 4-Simulation of Half Wave Controlled Rectifier Using Simulink In Matlab 00:26:00 Module 5- Principle of Operation of Fully Controlled Bridge Rectifier Part 1 00:06:00 Module 6- Principle of Operation of Fully Controlled Bridge Rectifier Part 2 00:06:00 Module 7-Simulation of Bridge Controlled Rectifier 00:16:00 Module 8-AC Chopper with R Load Principle of Operation 00:14:00 Module 9- Simulation of AC Chopper with R and RL Loads in MATLAB 00:11:00 Module 10- Buck Regulator Principle of Operation Part 1 00:16:00 Module 11-Buck Regulator Principle of Operation Part 2 00:17:00 Module 12-Simulation of Buck Regulator in MATLAB 00:14:00 Module 13-Boost Regulator Principle of Operation 00:23:00 Module 14- Simulation of Boost Regulator in MATLAB 00:12:00 Module 15-Buck-Boost Regulator Principle of Operation 00:17:00 Module 16- Simulation of Buck-Boost Regulator 00:09:00 Module 17- Single Phase Half Bridge R-Load 00:15:00 Module 18- Single Phase Half Bridge RL-Load 00:08:00 Module 19-Simulation of Single Phase Half Bridge Inverter 00:18:00 Module 20-Single Phase Bridge Inverter R-Load 00:06:00 Module 21-Single Phase Bridge Inverter RL-Load 00:07:00 Module 22-Simulation of Single Phase Bridge Inverter 00:10:00 Module 23-Three Phase Inverters and Obtaining The Line Voltages 00:15:00 Module 24-Three Phase Inverters and Obtaining The Phase Voltages 00:17:00 Module 25-Simulation of Three Phase Inverter 00:17:00 Module 26-Simulation of Charging and Discharging Capacitor Using Matlab 00:10:00 Unit 3- Solar Energy Simulation Using Simulink in MATLAB Module 1-Separately Excited DC Machine 00:21:00 Module 2-DC Motor Modelling without Load Using Simulink in MATLAB 00:25:00 Module 3-DC Motor Modelling with Load Using Simulink in MALTAB 00:23:00 Module 4-DC Motor Block Simulation Using Power Library in MATLAB 00:16:00 Unit 4- DC Motor Simulation Using Simulink in MATLAB Module 1-Construction and Principle of Operation of Synchronous Generator 00:29:00 Module 2-Equivalent Circuit and Phasor Diagram of Non Salient Synchronous Machine 00:29:00 Module 3-Equivalent Circuit and Phasor Diagram of Salient Synchronous Machine 00:39:00 Module 4-Simulation of Synchronous Machine Connected to Small Power System 00:38:00 Unit 5- Induction Motor Simulation Using Simulink in MATLAB 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- Simulation of Induction Motor or Asynchronous Motor Using Simulink 00:33:00 Unit 6- Synchronous Generator Simulation in Simulink of MATLAB Module 1- Importing Data from PSCAD Program for Fault Location Detection to MATLAB Program 00:37:00 Unit 7- Power System Simulations Module 1-How to Implement PID Controller in Simulink of MATLAB 00:14:00 Module 2-Tuning a PID Controller In MATLAB Simulink 00:17:00 Assignment Assignment - MATLAB Simulink for Electrical Power Engineering 00:00:00