R Programming A-Z™: R For Data Science With Real Exercises!

Learn Programming In R And R Studio. Data Analytics, Data Science, Statistical Analysis, Packages, Functions, GGPlot2

What you'll learn

Learn to program in R at a good level

Learn how to use R Studio

Learn the core principles of programming

Learn how to create vectors in R

Learn how to create variables

Learn about integer, double, logical, character and other types in R

Learn how to create a while() loop and a for() loop in R

Learn how to build and use matrices in R

Learn the matrix() function, learn rbind() and cbind()

Learn how to install packages in R

Learn how to customize R studio to suit your preferences

Understand the Law of Large Numbers

Understand the Normal distribution

Practice working with statistical data in R

Practice working with financial data in R

Practice working with sports data in R

Requirements

No prior knowledge or experience needed. Only a passion to be successful!

Description

Learn R Programming by doing!There are lots of R courses and lectures out there. However, R has a very steep learning curve and students often get overwhelmed. This course is different!This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward.After every video, you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises.In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course!I can't wait to see you in class,What you will learn:Learn how to use R StudioLearn the core principles of programmingLearn how to create vectors in RLearn how to create variablesLearn about integer, double, logical, character, and other types in RLearn how to create a while() loop and a for() loop in RLearn how to build and use matrices in RLearn the matrix() function, learn rbind() and cbind()Learn how to install packages in RSincerely,Kirill Eremenko

Overview

Section 1: Hit The Ground Running

Lecture 1 Welcome to the R Programming Course!

Lecture 2 Updates on Udemy Reviews

Lecture 3 Installing R and R Studio (MAC & Windows)

Lecture 4 Exercise - Get Excited!

Lecture 5 Get the Datasets here

Lecture 6 Extra Resources

Section 2: Core Programming Principles

Lecture 7 Welcome to this section. This is what you will learn!

Lecture 8 Types of variables

Lecture 9 Using Variables

Lecture 10 Logical Variables and Operators

Lecture 11 The "While" Loop

Lecture 12 Using the console

Lecture 13 The "For" Loop

Lecture 14 The "If" statement

Lecture 15 Section Recap

Lecture 16 HOMEWORK: Law of Large Numbers

Section 3: Fundamentals Of R

Lecture 17 Welcome to this section. This is what you will learn!

Lecture 18 What is a Vector?

Lecture 19 Let's create some vectors

Lecture 20 Using the [] brackets

Lecture 21 Vectorized operations

Lecture 22 The power of vectorized operations

Lecture 23 Functions in R

Lecture 24 Packages in R

Lecture 25 Section Recap

Lecture 26 HOMEWORK: Financial Statement Analysis

Section 4: Matrices

Lecture 27 Welcome to this section. This is what you will learn!

Lecture 28 Project Brief: Basketball Trends

Lecture 29 Matrices

Lecture 30 Building Your First Matrix

Lecture 31 Naming Dimensions

Lecture 32 Colnames() and Rownames()

Lecture 33 Matrix Operations

Lecture 34 Visualizing With Matplot()

Lecture 35 Subsetting

Lecture 36 Visualizing Subsets

Lecture 37 Creating Your First Function

Lecture 38 Basketball Insights

Lecture 39 Section Recap

Lecture 40 HOMEWORK: Basketball Free Throws

Section 5: Data Frames

Lecture 41 Welcome to this section. This is what you will learn!

Lecture 42 Project Brief: Demographic Analysis

Lecture 43 Importing data into R

Lecture 44 Exploring your dataset

Lecture 45 Using the $ sign

Lecture 46 Basic operations with a Data Frame

Lecture 47 Filtering a Data Frame

Lecture 48 Introduction to qplot

Lecture 49 Visualizing With Qplot: Part I

Lecture 50 Building Dataframes

Lecture 51 Merging Data Frames

Lecture 52 Visualizing With Qplot: Part II

Lecture 53 Section Recap

Lecture 54 HOMEWORK: World Trends

Section 6: Advanced Visualization With GGPlot2

Lecture 55 Welcome to this section. This is what you will learn!

Lecture 56 Project Brief: Movie Ratings

Lecture 57 Grammar Of Graphics - GGPlot2

Lecture 58 What is a Factor?

Lecture 59 Aesthetics

Lecture 60 Plotting With Layers

Lecture 61 Overriding Aesthetics

Lecture 62 Mapping vs Setting

Lecture 63 Histograms and Density Charts

Lecture 64 Starting Layer Tips

Lecture 65 Statistical Transformations

Lecture 66 Using Facets

Lecture 67 Coordinates

Lecture 68 Perfecting By Adding Themes

Lecture 69 Section Recap

Lecture 70 HOMEWORK: Movie Domestic % Gross

Section 7: Homework Solutions

Lecture 71 Homework Solution Section 2: Law Of Large Numbers

Lecture 72 Homework Solution Section 3: Financial Statement Analysis

Lecture 73 Homework Solution Section 4: Basketball Free Throws

Lecture 74 Homework Solution Section 5: World Trends

Lecture 75 Homework Solution Section 6: Movie Domestic % Gross (Part 1)

Lecture 76 Homework Solution Section 6: Movie Domestic % Gross (Part 2)

Lecture 77 THANK YOU bonus video

Section 8: Bonus Tutorials

Lecture 78 BoxPlots

Lecture 79 **YOUR SPECIAL BONUS**

This course is for you if you want to learn how to program in R,This course is for you if you are tired of R courses that are too complicated,This course is for you if you want to learn R by doing ,This course is for you if you like exciting challenges,You WILL have homework in this course so you have to be prepared to work on it