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

R (programming language)

Data Science

Development

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

4.5

(56368)

281074 enrolled on this course

Last updated 11/2021

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₹ 4999.0

₹ 6499.0

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Lessons

Quizzes

Duration

13 Hours

Skill level

Beginner

Language

English

Certificate

Yes

Full lifetime access

Yes

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 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
Sincerely,
Kirill Eremenko
Who this course is for:
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

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

You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
No previous design experience is needed.
No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures

Expand All Sections

1-Hit The Ground Running

1.1-Welcome Challenge!

1.2-Welcome to the R Programming Course!

1.3-Installing R and R Studio (MAC & Windows)

1.4-Exercise - Get Excited!

1.5-Get the Datasets here

1.6-Extra Resources

2-Core Programming Principles

2.1-Welcome to this section. This is what you will learn!

2.2-Types of variables

2.3-Using Variables

2.4-Logical Variables and Operators

2.5-The "While" Loop

2.6-Using the console

2.7-The "For" Loop

2.8-The "If" statement

2.9-Section Recap

2.10-HOMEWORK: Law of Large Numbers

2.11-Core Programming Principles

3-Fundamentals Of R

3.1-Welcome to this section. This is what you will learn!

3.2-What is a Vector?

3.3-Let's create some vectors

3.4-Using the [] brackets

3.5-Vectorized operations

3.6-The power of vectorized operations

3.7-Functions in R

3.8-Packages in R

3.9-Section Recap

3.10-HOMEWORK: Financial Statement Analysis

3.11-Fundamentals of R

4-Matrices

4.1-Welcome to this section. This is what you will learn!

4.2-Project Brief: Basketball Trends

4.3-Matrices

4.4-Building Your First Matrix

4.5-Naming Dimensions

4.6-Colnames() and Rownames()

4.7-Matrix Operations

4.8-Visualizing With Matplot()

4.9-Subsetting

4.10-Visualizing Subsets

4.11-Creating Your First Function

4.12-Basketball Insights

4.13-Section Recap

4.14-HOMEWORK: Basketball Free Throws

4.15-Matrices

5-Data Frames

5.1-Welcome to this section. This is what you will learn!

5.2-Project Brief: Demographic Analysis

5.3-Importing data into R

5.4-Exploring your dataset

5.5-Using the $ sign

5.6-Basic operations with a Data Frame

5.7-Filtering a Data Frame

5.8-Introduction to qplot

5.9-Visualizing With Qplot: Part I

5.10-Building Dataframes

5.11-Merging Data Frames

5.12-Visualizing With Qplot: Part II

5.13-Section Recap

5.14-HOMEWORK: World Trends

5.15-Data Frames

6-Advanced Visualization With GGPlot2

6.1-Welcome to this section. This is what you will learn!

6.2-Project Brief: Movie Ratings

6.3-Grammar Of Graphics - GGPlot2

6.4-What is a Factor?

6.5-Aesthetics

6.6-Plotting With Layers

6.7-Overriding Aesthetics

6.8-Mapping vs Setting

6.9-Histograms and Density Charts

6.10-Starting Layer Tips

6.11-Statistical Transformations

6.12-Using Facets

6.13-Coordinates

6.14-Perfecting By Adding Themes

6.15-Section Recap

6.16-HOMEWORK: Movie Domestic % Gross

6.17-Advanced Visualization With GGPlot2

7-Homework Solutions

7.1-Homework Solution Section 2: Law Of Large Numbers

7.2-Homework Solution Section 3: Financial Statement Analysis

7.3-Homework Solution Section 4: Basketball Free Throws

7.4-Homework Solution Section 5: World Trends

7.5-Homework Solution Section 6: Movie Domestic % Gross (Part 1)

7.6-Homework Solution Section 6: Movie Domestic % Gross (Part 2)

7.7-THANK YOU Video

8-Special Offer

8.1-BoxPlots

9-Congratulations!! Don't forget your Prize :)

9.1-Huge Congrats for completing the challenge!

9.2-Bonus: How To UNLOCK Top Salaries (Live Training)

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