10 Best Free R Programming Courses You Must Know in 2024

Are you looking for the Best Free R Programming Courses?… If yes, then this article is for you. In this article, you will find the 10 Best Free R Programming Courses. All the courses are free and you don’t need to pay for any course.

So without any further ado, let’s get started-

Best Free R Programming Courses

1.  Data Analysis with R– Udacity

Rating-	NA
Time to Complete-	2 Months
Best For-	Intermediate

This is an intermediate-level free course to learn data analysis using R programming. This course has 10 lessons including one final project. The course begins with an explanation of EDA (exploratory data analysis) and the goals of EDA. In the next lesson, you will learn the basics of R Programming.

Next, there are some lessons on exploring one variable, two variables, and many variables. And there are problem sets associated with each lesson. For eg. a problem set for exploring one variable, a problem set for exploring two and many variables.

After that, you will learn Linear Regression Models and predict diamond prices using other variables in the diamonds dataset. In the end, there is one final project where you have to use R and apply exploratory data analysis techniques to explore relationships in one variable to multiple variables.

Most of the time, free courses lack content quality but this course is full of knowledge and covers some advanced concepts with quizzes, practice sets, and projects.

Drawback-

• Doesn’t provide a certificate.

You Should Enroll if-

• You have prior knowledge of statistics.

Interested to Enroll?

If yes, then start learning- Data Analysis with R

2. Data Analysis and Visualization– Udacity

Rating-	NA
Time to Complete-	16 weeks
Best For-	Intermediate

This is another free course for learning data analysis and visualization. R programming language is used in this course. The course starts with an introduction to R Programming. Then, you will learn some advanced concepts of R programming.

After that, you will learn data visualization basics and ggplot2. There are various quizzes in each lesson. These quizzes will help you to test your knowledge.

This course also covers Logistic Regression, Linear Regression, and Regularization. Overall, this course is more practical in nature. You will learn by working on problem sets. This course also has a series of Netflix Interview videos.

Drawback-

• You will not receive a certificate.

You Should Enroll if-

• You have prior programming experience and are familiar with mathematics (basic linear algebra, calculus, introductory probability).

Interested to Enroll?

If yes, then start learning- Data Analysis and Visualization.

3. R Programming– Coursera

Rating-	4.5/5
Time to Complete-	57 hours
Best For-	Intermediate

This is a Free to Audit course on Coursera. That means you can access the course material free of cost, but for the certificate, you have to pay.

To audit this course for free, click on the “Enroll for Free” button. A new popup window will appear, where they ask you to choose the subscription months. But on the same page, in the bottom left corner, there is an option “Audit the course”. Choose this option, and you will be redirected to the course materials free of cost.

This course has a 4-week study plan. In week 1, R programming basics are covered and there are practical R exercises in a swirl. In week 2, you will learn the control structures, functions, dates, and times in R programming.

Week 3 covers loop functions and debugging tools in R. The last week is all about simulation and profiling. You will learn R profiler.

Drawback-

• The course quizzes are locked for the free course.

You Should Enroll if-

• You have basic regression knowledge and want to learn only the Basics of R Programming.

Interested to Enroll?

If yes, then start learning- R Programming 

4. Data Analysis with R Programming- Coursera

Rating-	4.8/5
Time to Complete-	37 hours
Best For-	Beginner

This is a Free to Audit course on Coursera. That means you can access the course material free of cost, but for the certificate, you have to pay.

To audit this course for free, click on the “Enroll for Free” button. A new popup window will appear, where they ask you to choose the subscription months. But on the same page, in the bottom left corner, there is an option “Audit the course”. Choose this option, and you will be redirected to the course materials free of cost.

This course has a 5-week study plan. In the first week, you will get an introduction to R and Rstudio. The next week focuses on more R programming topics such as vectors, lists, dates, times, common data structure, and operators in R Programming. You will also learn tidyverse.

Week 3 is more practical where you will learn data in R, R dataframes, how to clean the data, how to transform the data, and how to organize the data using R Programming.

Week 4 is all about data visualization using R programming, and Week 5 will cover how to use R Markdown in RStudio. Overall, this is a good course for understanding how data analysis and visualization are performed using the R Programming language.

Drawback-

• The challenges and quizzes are locked in free mode.

You Should Enroll if-

• You have no prior experience with spreadsheets or data analytics.

Interested to Enroll?

If yes, then start learning- Data Analysis with R Programming

5. Introduction to R Programming for Data Science- Coursera

Rating-	4.4/5
Time to Complete-	10 hours
Best For-	Beginner

To audit this course for free, click on the “Enroll for Free” button. A new popup window will appear, where they ask you to choose the subscription months. But on the same page, in the bottom left corner, there is an option “Audit the course”. Choose this option, and you will be redirected to the course materials free of cost.

This course also has a 5-week study plan. Week 1 is all about R programming basics. In week 2, you will learn vectors, factors, lists, arrays, and matrices in R programming.

In week 3, you will learn conditions, loops, functions, regular expressions, and date format in R. Week 4 teaches you how to read text files in R, how to write and save to files, and web scrapping in R.

The last week is all about the capstone project but if you enroll in this course for free, you can’t access the project.

Drawback-

• You will not receive a certificate.

You Should Enroll if-

• You have no prior knowledge of R.

Interested to Enroll?

If yes, then start learning- Introduction to R Programming for Data Science

6. Introduction to R- DataCamp

Rating-	4.7/5
Time to Complete-	4hrs
Best For-	Beginner

In this course, you will learn the fundamentals of R programming, a powerful language for data analysis. Starting with the basics, you will discover how to use R as a calculator and understand different data types. You will then progress to creating and manipulating vectors, essential tools for data tasks.

Delving deeper, you will explore matrices and their calculations in R, gaining valuable skills for handling data more efficiently. Understand how R manages categorical data with factors and apply this knowledge in real-world scenarios. Additionally, you will master working with R data frames and lists, crucial for advanced data manipulation.

Upon completion, you will have a solid foundation in R programming, enabling you to perform basic tasks and embark on more complex data analyses. This course acts as a gateway to specialized tracks like Data Analyst with R or Data Scientist. Acquiring R skills will enhance your capabilities in the job market.

Drawback-

• This course needs more real-world examples and hands-on activities. Right now, there aren’t many chances to apply what you learn to actual situations, which might make it harder to use these skills in real-life data tasks.

You Should Enroll if-

• You are a beginner and want to learn R Programming.

Interested to Enroll?

If yes, then start learning- Introduction to R

7. Introduction to Importing Data in R- DataCamp

Rating-	4.2/5
Time to Complete-	3 hrs
Best For-	Beginner

In this course, you will learn the essential skill of effortlessly importing data into R for analysis. This step, often a stumbling block, becomes a breeze as you gain expertise in handling various formats—.csv, text files, statistical software files, databases, and HTML data. Understanding the right approach is crucial to kickstarting your actual analysis.

You will start by mastering the process of reading .csv and text files in R. Then, delve into the readr and data.table packages, discovering efficient ways to import flat file data. Finally, unlock the capability to read .xls files in R using readxl and gdata.

By the course’s end, you will have acquired the skills to seamlessly handle diverse data formats, ensuring a smooth transition from raw data to insightful analysis.

Drawback-

• The course misses out on teaching about fancy data types like JSON or databases. It would be better if it included these, so you’re ready for all kinds of real-life data.

You Should Enroll if-

• You have a basic understanding of R programming.

Interested to Enroll?

If yes, then start learning- Introduction to Importing Data in R

8. Intermediate R- DataCamp

Rating-	4.5/5
Time to Complete-	6 hrs
Best For-	Beginner

In this Intermediate R course, you will learn to level up your R programming skills. Dive into conditional statements, loops, and functions, gaining the tools to create your own R scripts. Discover the power of apply functions to make your R code more efficient and readable.

In the utilities chapter, you will learn essential skills like using regular expressions, manipulating data structures, and handling times and dates. This course is your opportunity to take the next step in advancing your overall knowledge and capabilities while programming in R.

Drawback-

• The course doesn’t go into super advanced things beyond basics. It would be better if it included more tricky topics to make you ready for tougher R programming tasks.

You Should Enroll if-

• You have a basic understanding of R programming.

Interested to Enroll?

If yes, then start learning- Intermediate R

9. R Basics – R Programming Language Introduction- Udemy

Rating-	4.6/5
Time to Complete-	4hr 6min
Best For-	Beginner

This Free Udemy course has 3 sections. In the first section, you will learn R basics and how to download R and Rstudio. In the next section, you will learn how to code in R programming and understand functions, loops, R datasets, and R dataframes.

The last section teaches how to load CSV files in R, how to apply a family of functions, how to test for normality, KNN classification, LDA(Linear Discriminant Analysis), etc.

Overall, this is a good course for beginners to learn R programming basics.

Drawback-

• The course is not in-depth and covers only the basics.

You Should Enroll if-

• You have a basic understanding of statistics and data structure.

Interested to Enroll?

If yes, then start learning- R Basics – R Programming Language Introduction

10. R, ggplot, and Simple Linear Regression- Udemy

Rating-	4.6/5
Time to Complete-	2hr 14min
Best For-	Beginner

Rating- 4.6/5

Time to Complete- 2hr 14min

This free course will help you to learn R. This course has 4 sections. The first section covers how to install R and R studio. The next section explains ggplot2, plotting a point with ggplot, graphing lines with ggplot, etc.

In section 3, you will learn about normal populations, how to plot a vertical sample, a cloud of points, etc. And the last section will cover Simple Linear Regression.

Drawback-

• Doesn’t provide a certificate.

You Should Enroll if-

• You are a beginner and interested in learning R, ggplot2, and the basics of linear regression.

Interested to Enroll?

If yes, then start learning- R, ggplot, and Simple Linear Regression

That’s all!

Summary of 10 Best Free R Programming Courses

Course Name	Rating	Time to Complete
1.  Data Analysis with R– Udacity	NA	2 Months
2. Data Analysis and Visualization– Udacity	NA	16 Weeks
3. R Programming– Coursera	4.5/5	57 hours
4. Data Analysis with R Programming– Coursera	4.8/5	37 hours
5. Introduction to R Programming for Data Science– Coursera	4.4/5	12 hours
6. Introduction to R– DataCamp	4.7/5	4 hours
7. Introduction to Importing Data in R– DataCamp	4.2/5	3 hours
8. Intermediate R– DataCamp	4.5/5	6 hours
9. R Basics – R Programming Language Introduction– Udemy	4.6/5	4hr 6min
10. R, ggplot, and Simple Linear Regression– Udemy	4.6/5	2hr 14min

These are the 10 Best Free R Programming Courses.

My Recommendation

I would recommend Data Analysis and Visualization by Udacity. Because the course covers R programming basics along with data analysis and data visualization concepts. There are various quizzes in the course.

Now, it’s time to wrap up.

Conclusion

I hope these 10 Best Free R Programming Courses will help you to learn R Programming. My aim is to provide you with the best resources for Learning. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Happy Learning!

Thank YOU!

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