R Programming for Data Science

categories: Technology, Science & Productivity

Digital

Technology

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By the end of this course, you will be able to

Use the R working tools and environment for professionals and the R syntax. Then, you will learn how to explain and describe the code by using comments.
Perform mathematical operations, type conversion, built-in functions, and many useful built-in functions for math operations. Then, you will learn about variables, values, and assignments.
Handle different operations on variables and values using operators, and use data visualizations and graphics in R: drawing points, line plotting, pie charts, and more.

Course details

5 h 7 m/96 lessons
Last updated: 1/5/2023
Course completion certificate

Course Content

Free lessons

Course Intro

4 Minutes

Variables in detail 1

3 Minutes

Downloading and Installing R

5 Minutes

Variables in detail 2

3 Minutes

Downloading and Installing the RStudio IDE

6 Minutes

Variables in detail 3

3 Minutes

Setup working directory

1 Minutes

Variables in detail 4

2 Minutes

Data Types 1

2 Minutes

10.

Data Types 2

3 Minutes

1. Introduction

Course Intro

4 Minutes

Downloading and Installing R

5 Minutes

Downloading and Installing the RStudio IDE

6 Minutes

Setup working directory

1 Minutes

2. Variables, Data Types and Hints

Variables in detail 1

3 Minutes

Variables in detail 2

3 Minutes

Variables in detail 3

3 Minutes

Variables in detail 4

2 Minutes

Data Types 1

2 Minutes

Data Types 2

3 Minutes

Data Types 3

2 Minutes

Code hints

2 Minutes

3. Numbers and Math

Type of numbers

8 Minutes

Type Conversion

7 Minutes

Math operations

9 Minutes

4. Characters

Strings 1

3 Minutes

Strings 2

2 Minutes

Strings 3

3 Minutes

Strings 4

1 Minutes

Strings 5

1 Minutes

Strings 6

1 Minutes

Strings 7

2 Minutes

5. Logical and operators

Logical values 1

1 Minutes

Logical values 2

4 Minutes

Operators 1

1 Minutes

Operators 2

3 Minutes

Operators 3

2 Minutes

Operators 4

2 Minutes

Operators 5

3 Minutes

6. DS – Vectors

Vectors 1

1 Minutes

Vectors 2

3 Minutes

Vectors 3

3 Minutes

Vectors 4

3 Minutes

Vectors 5

4 Minutes

Vectors 6

2 Minutes

Vectors 7

1 Minutes

7. DS – Lists

Lists 1

2 Minutes

Lists 2

4 Minutes

Lists 3

4 Minutes

Lists 4

4 Minutes

8. DS – Matrices

DS - Matrices 1

1 Minutes

DS - Matrices 2

3 Minutes

DS - Matrices 3

4 Minutes

DS - Matrices 4

6 Minutes

DS - Matrices 5

2 Minutes

9. DS – Arrays

DS - Arrays 1

DS - Arrays 2

2 Minutes

DS - Arrays 3

1 Minutes

DS - Arrays 4

3 Minutes

DS - Arrays 5

3 Minutes

10. DS - Data Frame

DS - Data Frame 1

1 Minutes

DS - Data Frame 2

3 Minutes

DS - Data Frame 3

2 Minutes

DS - Data Frame 4

5 Minutes

DS - Data Frame 5

2 Minutes

DS - Data Frame 6

3 Minutes

11. DS – Factors

DS - Factors 1

1 Minutes

DS - Factors 2

5 Minutes

DS - Factors 3

2 Minutes

DS - Factors 4

3 Minutes

12. Decision making

Conditional statements 1

2 Minutes

Conditional statements 2

3 Minutes

Conditional statements 3

2 Minutes

Conditional statements 4

3 Minutes

13. Repetition

While loop 1

1 Minutes

While loop 2

3 Minutes

While loop 3

2 Minutes

For loop 1

1 Minutes

For loop 2

2 Minutes

For loop 3

5 Minutes

For loop 4

2 Minutes

14. Functional Programming

Functions 1

1 Minutes

Functions 2

3 Minutes

Functions 3

5 Minutes

Functions 4

2 Minutes

Functions 5

5 Minutes

15. Statistics and Data analysis

Statistics and data analysis 1

1 Minutes

Statistics and data analysis 2

8 Minutes

Statistics and data analysis 3

3 Minutes

Statistics and data analysis 4

3 Minutes

Statistics and data analysis 5

2 Minutes

16. Data Visualization and Graphics

Plotting in R 1

Plotting in R 2

4 Minutes

Plotting in R 3

3 Minutes

Plotting in R 4

1 Minutes

Lines 1

Lines 2

3 Minutes

Lines 3

3 Minutes

Pie Charts 1

Pie Charts 2

2 Minutes

10.

Pie Charts 3

5 Minutes

11.

Bars and Histograms 1

1 Minutes

12.

Bars and Histograms 2

2 Minutes

13.

Bars and Histograms 3

1 Minutes

14.

Bars and Histograms 4

2 Minutes

15.

Bars and Histograms 5

2 Minutes

About this course

R is one of the most powerful programming languages, for statistical computing and graphical presentation to analyze and visualize data. Therefore, in this training course, you will learn how to code with R from the R basics to the R advanced concepts. You will also explore how the R programming language can be used today for data analysis and the production of beautiful data visualizations and graphics.

Course requirements and prerequisites

There are no requirements for this course. Your interest in the topic and your commitment to learning are all you need to achieve the utmost benefit from this course.