4.61 out of 5
4.61
41002 reviews on Udemy

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
Instructor:
Kirill Eremenko
209,348 students enrolled
English More
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

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,

Sincerely,

Kirill Eremenko

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
BONUS: Learning Paths
5
Exercise - Get Excited!
6
Get the materials
7
Some Additional Resources!!
8
BONUS: Interview with Hadley Wickham
9
Your Shortcut To Becoming A Better Data Scientist!

Core Programming Principles

1
Welcome to this section. This is what you will learn!
2
Types of variables
3
Using Variables
4
Logical Variables and Operators
5
The "While" Loop
6
Using the console
7
The "For" Loop
8
The "If" statement
9
Section Recap
10
HOMEWORK: Law of Large Numbers
11
Core Programming Principles

Fundamentals Of R

1
Welcome to this section. This is what you will learn!
2
What is a Vector?
3
Let's create some vectors
4
Using the [] brackets
5
Vectorized operations
6
The power of vectorized operations
7
Functions in R
8
Packages in R
9
Section Recap
10
HOMEWORK: Financial Statement Analysis
11
Fundamentals of R

Matrices

1
Welcome to this section. This is what you will learn!
2
Project Brief: Basketball Trends
3
Matrices
4
Building Your First Matrix
5
Naming Dimensions
6
Colnames() and Rownames()
7
Matrix Operations
8
Visualizing With Matplot()
9
Subsetting
10
Visualizing Subsets
11
Creating Your First Function
12
Basketball Insights
13
Section Recap
14
HOMEWORK: Basketball Free Throws
15
Matrices

Data Frames

1
Welcome to this section. This is what you will learn!
2
Project Brief: Demographic Analysis
3
Importing data into R
4
Exploring your dataset
5
Using the $ sign
6
Basic operations with a Data Frame
7
Filtering a Data Frame
8
Introduction to qplot
9
Visualizing With Qplot: Part I
10
Building Dataframes
11
Merging Data Frames
12
Visualizing With Qplot: Part II
13
Section Recap
14
HOMEWORK: World Trends
15
Data Frames

Advanced Visualization With GGPlot2

1
Welcome to this section. This is what you will learn!
2
Project Brief: Movie Ratings
3
Grammar Of Graphics - GGPlot2
4
What is a Factor?
5
Aesthetics
6
Plotting With Layers
7
Overriding Aesthetics
8
Mapping vs Setting
9
Histograms and Density Charts
10
Starting Layer Tips
11
Statistical Transformations
12
Using Facets
13
Coordinates
14
Perfecting By Adding Themes
15
Section Recap
16
HOMEWORK: Movie Domestic % Gross
17
Advanced Visualization With GGPlot2

Homework Solutions

1
Homework Solution Section 2: Law Of Large Numbers
2
Homework Solution Section 3: Financial Statement Analysis
3
Homework Solution Section 4: Basketball Free Throws
4
Homework Solution Section 5: World Trends
5
Homework Solution Section 6: Movie Domestic % Gross (Part 1)
6
Homework Solution Section 6: Movie Domestic % Gross (Part 2)
7
THANK YOU bonus video

Bonus Tutorials

1
BoxPlots
2
**YOUR SPECIAL BONUS**
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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11 hours on-demand video
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Certificate of Completion
R Programming A-Z™: R For Data Science With Real Exercises!
Price:
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