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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
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Course Curriculum Building Your Body You Want Module 01: Introduction 00:02:00 Module 02: Disclaimer PDF 00:02:00 Module 03: Overview of the 10 commonly asked questions 00:04:00 Module 04: Question 1 00:03:00 Module 05: What is a Mitochondrion and why are they essential for health. What fuel does it need and where does the fuel come from? 00:03:00 Module 06: All about carbohydrates and where the body stores the excess plus the hormones the body needs to metabolize carbohydrates 00:04:00 Module 07: Insulin. What is it and why is it important? What is a normal response to insulin and what happens to fuel supply when we are sleeping? 00:05:00 Module 08: Fats and when they are burned 00:04:00 Module 09: Question 2 00:01:00 Module 9A: Practical examples of how the fat creeps on 00:06:00 Module 10: Dangers of Fructose and where does it hide? 00:03:00 Module 11: Question 3 00:07:00 Module 12: Summary so far. What is the number 1 change to make and what hormones are our 'fat' hormones? 00:02:00 Module 13: Fat making hormone no 1. Insulin and Insulin Resistance. How can one hormone make me fat? 00:05:00 Module 14: First Impactful change. How to start influencing insulin? 00:04:00 Module 15: Question 4 00:04:00 Module 16: What about Insulin and Leptin resistance? Why should that make me hungry and what nutrients are best to get rid of cravings? 00:03:00 Module 17: Impactful change no 2. Important supplements for weight loss, dosages and summary of changes so far. 00:05:00 Module 18: Question 5 00:01:00 Module 19: More about those enzymes and how they act and what role does insulin play on their action? 00:05:00 Module 20: Perspective summary 00:02:00 Module 21: Third Impactful change. Eliminating Carbohydrates. What can I eat and what must I avoid? 00:02:00 Module 22: Glycemic Index vs Glycemic load 00:01:00 Module 23: Carbohydrates to eat and carbohydrates to avoid 00:01:00 Module 24: Question 6 00:03:00 Module 25: More dangers associated with Insulin Resistance and why does this increase my risk of developing Diabetes? 00:03:00 Module 26: Question 7 00:05:00 Module 27: Glucose Management 00:01:00 Module 28: Intermittent Fasting. Will this benefit me and how do I do this without going hungry? 00:05:00 Module 29: Intermittent Fasting 00:01:00 Module 30: When do I exercise to maximize the benefit? 00:02:00 Module 31: What exercises can I do that won't take ages? 00:07:00 Module 32: High Interval Training 00:01:00 Module 33: Tabata Training 00:01:00 Module 34: Fourth and Fifth impactful change: Small changes: Big Impact 00:01:00 Module 35: Question 8 00:04:00 Module 37: Leptin Resistance. How does Leptin affect my metabolic rate? How does Leptin sabotage my weight loss? 00:03:00 Module 38: Question 9 00:04:00 Module 39: Practical reality example. 00:03:00 Module 40: Hunger and weight loss. Why never to go hungry. Complications of calorie restriction. 00:05:00 Module 41: What about protein? Is it important and how much is ideal? 00:05:00 Module 42: Protein for breakfast 00:01:00 Module 43: Common Proteins. 00:01:00 Module 44: Question 10 00:04:00 Module 45: How can I reduce my stress levels? What needs to change to get better sleep? 00:04:00 Module 46: Eat with Attention. 00:01:00 Module 47: Stress Management. 00:01:00 Module 48: Sleep aids. 00:01:00 Module 49: Big picture perspective and getting started. 00:03:00 Module 50: Summary of 10 small changes that have a big impact. 00:02:00 Module 51: 10 Changes PDF 00:01:00 Module 52: List of PDF's 00:01:00 Module 53: Thanks, and contact details for personal contact. 00:01:00 Module 54: 10 Readiness Strategies PDF 00:24:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00
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