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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

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Master the process of identifying and mitigating risks in any setting. This comprehensive Risk Assessment Course equips you with the skills to proactively manage potential threats, ensuring safety, compliance, and success. Enroll now and gain valuable knowledge for various industries.

Dive deeper into the world of mathematics with our 'Advanced Mathematics' course. Explore complex concepts and problem-solving techniques that will challenge and expand your mathematical proficiency. Whether you're a student aiming for higher academic achievements or a professional seeking to strengthen your analytical skills, this course will equip you with the knowledge and tools to excel. Enroll now and unlock the next level of mathematical understanding and capability.

Unlock the power of numbers with our dynamic Mathematics Course. From foundational concepts to advanced theories, delve into the world of mathematics and sharpen your analytical skills. Whether you're a student looking to improve your grades or an enthusiast eager to explore mathematical wonders, this course offers engaging lessons and practical exercises to enhance your mathematical proficiency. Enroll now and discover the beauty and utility of mathematics.

Overview In the era where information is abundant and decisions are driven by data, have you ever pondered, 'what is machine learning?' or 'what is data science?' Dive into the realm of 'Data Science & Machine Learning with R from A-Z,' a comprehensive guide to unravel these complexities. This course effortlessly blends the foundational aspects of data science with the intricate depths of machine learning algorithms, all through the versatile medium of R. As the digital economy booms, the demand for machine learning jobs continues to surge. Equip yourself with the proficiency to navigate this dynamic field and transition from being an inquisitive mind to a sought-after professional in the space of data science and machine learning with R. Learning Outcomes: Understand the foundational concepts of data science and machine learning. Familiarise oneself with the R environment and its functionalities. Master data types, structures, and advanced techniques in R. Acquire proficiency in data manipulation and visual representation using R. Generate comprehensive reports using R Markdown and design web applications with R Shiny. Gain a thorough understanding of machine learning methodologies and their applications. Gain insights into initiating a successful career in the data science sector. Why buy this Data Science & Machine Learning with R from A-Z course? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Data Science & Machine Learning with R from A-Z 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 Data Science & Machine Learning with R from A-Z course for? This course is ideal for Individuals keen on exploring the intricacies of machine learning and data science. Aspiring data analysts and scientists looking to specialise in Machine Learning with R. IT professionals aiming to diversify their skill set in the emerging data-driven market. Researchers seeking to harness the power of R for data representation and analysis. Academics and students aiming to bolster their understanding of modern data practices with R. Prerequisites This Data Science & Machine Learning with R from A-Z does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Science & Machine Learning with R from A-Z 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 Data Scientist - Average salary range: £35,000 - £70,000 Per Annum Machine Learning Engineer - Average salary range: £50,000 - £80,000 Per Annum Data Analyst - Average salary range: £28,000 - £55,000 Per Annum R Developer - Average salary range: £30,000 - £60,000 Per Annum R Shiny Web Developer - Average salary range: £32,000 - £65,000 Per Annum Machine Learning Researcher - Average salary range: £40,000 - £75,000 Per Annum Course Curriculum 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 Getting Started with R 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 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 Database 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 Assignment Assignment - Data Science & Machine Learning with R 00:00:00