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

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

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 79 lectures (10h 36m) | 4.84 GB

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

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 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
Table of Contents

Hit The Ground Running
1 Welcome to the R Programming Course
2 Updates on Udemy Reviews
3 Installing R and R Studio MAC & Windows
4 Exercise Get Excited
5 Get the Datasets here
6 Extra Resources

Core Programming Principles
7 Welcome to this section This is what you will learn
8 Types of variables
9 Using Variables
10 Logical Variables and Operators
11 The While Loop
12 Using the console
13 The For Loop
14 The If statement
15 Section Recap
16 HOMEWORK Law of Large Numbers

Fundamentals Of R
17 Welcome to this section This is what you will learn
18 What is a Vector
19 Lets create some vectors
20 Using the brackets
21 Vectorized operations
22 The power of vectorized operations
23 Functions in R
24 Packages in R
25 Section Recap
26 HOMEWORK Financial Statement Analysis

Matrices
27 Welcome to this section This is what you will learn
28 Project Brief Basketball Trends
29 Matrices
30 Building Your First Matrix
31 Naming Dimensions
32 Colnames and Rownames
33 Matrix Operations
34 Visualizing With Matplot
35 Subsetting
36 Visualizing Subsets
37 Creating Your First Function
38 Basketball Insights
39 Section Recap
40 HOMEWORK Basketball Free Throws

Data Frames
41 Welcome to this section This is what you will learn
42 Project Brief Demographic Analysis
43 Importing data into R
44 Exploring your dataset
45 Using the sign
46 Basic operations with a Data Frame
47 Filtering a Data Frame
48 Introduction to qplot
49 Visualizing With Qplot Part I
50 Building Dataframes
51 Merging Data Frames
52 Visualizing With Qplot Part II
53 Section Recap
54 HOMEWORK World Trends

Advanced Visualization With GGPlot2
55 Welcome to this section This is what you will learn
56 Project Brief Movie Ratings
57 Grammar Of Graphics GGPlot2
58 What is a Factor
59 Aesthetics
60 Plotting With Layers
61 Overriding Aesthetics
62 Mapping vs Setting
63 Histograms and Density Charts
64 Starting Layer Tips
65 Statistical Transformations
66 Using Facets
67 Coordinates
68 Perfecting By Adding Themes
69 Section Recap
70 HOMEWORK Movie Domestic Gross

Homework Solutions
71 Homework Solution Section 2 Law Of Large Numbers
72 Homework Solution Section 3 Financial Statement Analysis
73 Homework Solution Section 4 Basketball Free Throws
74 Homework Solution Section 5 World Trends
75 Homework Solution Section 6 Movie Domestic Gross Part 1
76 Homework Solution Section 6 Movie Domestic Gross Part 2
77 THANK YOU bonus video

Bonus Tutorials
78 BoxPlots
79 YOUR SPECIAL BONUS

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