Data science is one of the fastest-growing and most lucrative fields in the 21st century economy, so much so that it has been prominently and repeatedly referred to as “the new oil.” According to Glassdoor, the average yearly salary for data scientists is an impressive $117,345, while the highest earners make upwards of $150,000 per year.

If you’re interested in getting in on the new boom, you’re going to need to develop strong skills in commonly-used data science technologies. 

Learning R is a great place to start. R is a programming language used primarily for statistical analysis. Unlike more general use languages like Python and Java, R is used almost entirely for statistical computing and graphics. It is used daily by professionals in big data and statistics, such as data analysts, data scientists, and statisticians.

If you’ve never learned a programming language before, taking on a complex programming language like R can seem like an intimidating commitment. Fortunately, there are countless free and affordable online courses that will help you develop the basic skills to work with R in professional settings. We’ve put together a list of our favorite online courses to help you learn R on your own time, from the comfort of your home.

Beginner Courses on R

1. R Programming A-Z™: R for Data Science with Real Exercises!

This course is designed to help reduce R’s learning curve for beginner students, including those who have never worked with a programming language before. It primarily covers basic R concepts such as vectors, matrices, and data frames. For those who’ve never worked with any programming language before, it also includes introductory lessons on core programming principles like variables, functions, loops, and operators. In addition to R fundamentals, students will also learn some practical applications of R by working with different data sets — including sports data and financial data — in a series of exercises. At the end of the course, there is a series of lectures on data visualization using ggplot2.

• College credits: NO — Certificate of Completion only
• Price: $9.99 on sale ($199.99 regular price)
• Financial aid or scholarships: NO
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: 10 hours, 30 minutes
• Languages: English with subtitles in English, French, German, Indonesian, Italian, Japanese, Polish, Portuguese, Romanian, Spanish, and Turkish
• Vendor: Udemy

Note: Prices for all courses listed in this article are true on the date of publishing, but are subject to change.

2. R Programming for Statistics and Data Science

This is an introductory course that focuses specifically on using R for statistics and data science. It starts from scratch, covering the foundations of programming in R — data types, objects, functions, and more. It then steadily transitions into more advanced concepts. You’ll learn about manipulating data with the dplyr package and visualizing it with ggplot2. More than just an introduction to R, this course also includes lessons on various concepts in statistics, such as exploratory data analysis and linear regression analysis.

• College credits: NO — Certificate of Completion only
• Price: $9.99 on sale ($194.99 regular price)
• Financial aid or scholarships: NO
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: 6 hours, 30 minutes
• Languages: English with subtitles in English
• Vendor: Udemy

3. Data Science and Machine Learning Bootcamp with R

This course is a long, comprehensive introduction to R. It is designed for beginners, though by the end of the course, you will be working with some advanced concepts. The first half of the course covers programming in R and using R for data science. You’ll begin with basic concepts such as variables and vectors and steadily build the complexity. You’ll work with some advanced concepts like the “apply” functions and regular expressions. In the data science section, you’ll learn to use dplyr for data manipulation and ggplot2 for data visualization. The final section covers machine learning with R. You’ll cover a variety of machine learning concepts, such as linear regression, logistic regression, the k-nearest neighbors algorithm, decision trees and random forests, support vector machines, k-means clustering, natural language processing, and neural nets. In short, this is a great course for beginners who want to start learning R from scratch or intermediate-level R programmers interested in learning machine learning and some advanced data science and programming concepts.

• College credits: NO — Certificate of Completion only
• Price: $9.99 on sale (194.99 regular price)
• Financial aid or scholarships: NO
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: 17 hours, 30 minutes
• Languages: English with subtitles in English, Indonesian, Italian, Polish, Portuguese, Romanian, and Thai
• Vendor: Udemy

4. Data Science: R Basics

This course, designed by Harvard and available on EdX, is focused on building a foundational knowledge of programming with R. You’ll learn the R syntax and basic R programming concepts such as data types, vectors, arithmetic, and indexing. You’ll also learn about data wrangling using dplyr, data visualization using ggplot2, and more. Throughout the course, you’ll work with a real-world crime data set, allowing you to put the lessons into practice. The course is the first part of a HarvardX professional certificate in data science that later covers more complicated topics, such as probability, inference, regression, and machine learning.

• College credits: NO — Verified Certificate only
• Price: FREE to audit, but there’s a $219 fee to earn and buy a Verified Certificate
• Financial aid or scholarships: YES
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: 8 weeks (1–2 hours per week)
• Languages: English with subtitles in English
• Vendor: edX

Intermediate Courses on R

5. R Programming

This course, designed by Johns Hopkins University and available through Coursera, is designed for people who already have a familiarity with Python and understand the basic concepts of regression analysis. The course teaches R from scratch, beginning with lessons on installing R, the history of the programming language, and its fundamental concepts. By the end, you’ll be using R to simulate data and utilizing the profiler in R to optimize your programs. Though this course is an introduction to R, the assignments may be challenging for students new to programming and is recommended primarily for people with a background in computer science and prior programming experience.

• College credits: NO — Course Certificate only
• Price: FREE to audit, but there’s a fee to earn and buy a Course Certificate
• Financial aid or scholarship: YES
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: Approximately 20 hours 
• Languages: English with subtitles in English, Arabic, French, Chinese (Simplified), Portuguese (Brazilian), Vietnamese, Spanish, and Japanese
• Vendor: Coursera

6. Data Analysis with R

Designed by Facebook and available on Udemy, this course focuses on using R to perform exploratory data analysis (EDA). The course is composed of six lessons: “What is EDA?”, “R Basics”, “Explore One Variable”, “Explore Two Variables”, “Explore Multiple Variables,” and “Diamonds and Price Predictions.” The first couple of lessons are focused on teaching the fundamental concepts behind EDA and the R language. By the third lesson, you will already be putting these concepts into practice by working with pseudo-data sets of Facebook users. In the final section, you will learn about predictive modeling and complete on a final project in which you do your own exploratory data analysis on a data set of your choice In short, not only will you learn how to use R, but you will learn the theory and practice of EDA and put R into practice. Though this course doesn’t require a familiarity with R, you should have a familiarity with core principles of statistics and a competence with computer science and math concepts like variable assignment, comparison and logical operators, “if else” statements, and square roots, logarithms, and exponents.

• College credits: NO
• Price: FREE
• Financial aid or scholarships: YES
• Mobile learning: NO
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: Approximately 2 months
• Languages: English
• Vendor: Udacity

7. Graphs in R: Data Visualization With R Programming Language

This course is a short, but deep dive into data visualization with R. It is designed to introduce students to the complete graphical parameters of R. The course will walk you through different graphics packages you can use with R, including ggplot2, lattice, and plotrix. You’ll learn how to use these tools to build a variety of readable and presentable graphs. This is a great course for people who use R in their work and want to refine their graphical skills, including statisticians, data scientists, entrepreneurs, and students who work with data.

• College credits: NO — Certificate of Completion only
• Price: $9.99 on sale ($94.99 regular price)
• Financial aid or scholarships: NO
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: 3 hours, 30 minutes
• Languages: English with subtitles in English
• Vendor: Udemy

8. Mastering Data Visualization with R

This course is an in-depth look at using data visualization tools in R. In the three main sections, you will learn about three graphics packages: the base R package, the Lattice package, and the ggplot2 package. You will learn how to build a variety of graphs using each package, including histograms, density plots, box plots, bar charts, scatter plots, dot charts, strip charts, and more. There are introductory sections that briefly cover some of the foundational concepts, but you should already have a solid grasp of the fundamentals of working with R before taking the course.

• College credits: NO — Certificate of Completion only
• Price: $9.99 on sale ($144.99 regular price)
• Financial aid or scholarships: NO
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: 6 hours
• Languages: English with subtitles in English
• Vendor: Udemy

Advanced Courses on R

9. Advanced R Programming

This course from Johns Hopkins University teaches advanced concepts of R programming, such as functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions. The course is challenging, but a worthwhile investment for anybody who has experience with R and would like to go deeper. There are no visual lectures and assignments are difficult, but self-motivated students looking for a challenge will find it worthwhile.

• College credits: NO — Course Certificate only
• Price: FREE to audit, but there’s a fee to earn and buy a Course Certificate
• Financial aid or scholarship: YES
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: Approximately 11 hours 
• Languages: English with subtitles in English and Chinese (Simplified)
• Vendor: Coursera

10. R Programming: Advanced Analytics In R For Data Science

This course is largely a sequel to “R Programming A-Z™: R for Data Science with Real Exercises!,” designed and taught by the same instructor, Kirill Eremenko (described above). It skips over some topics covered in the introductory course such as the syntax and fundamental R concepts like vectors and dataframes. The course is oriented around grasping concepts used regularly in real-world data science. It is composed of three main sections: “Data Preparation,” “Lists in R” and “‘Apply’ Family of Functions”. Each of these sections is based on building industry relevant skills that you’ll use when working with real world data sets or building machine learning algorithms.

• College credits: NO — Certificate of Completion only
• Price: $9.99 on sale (199.99 regular price)
• Financial aid or scholarships: NO
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: 6 hours
• Languages: English with subtitles in English, French, German, Indonesian, Italian, Polish, and Romanian
• Vendor: Udemy

11. R Data Pre-Processing & Data Management – Shape Your Data!

This is an advanced course, designed largely for people who are used to working with R. It is focused on data pre-processing, a critical step in data analytics that is often overlooked in R tutorials. The lessons start at the very beginning, covering various ways of importing data into R, selecting the object class, and organizing the data into a clean format. The course then covers a variety of related subjects, including querying and filtering, data joins, using SQL in R, outlier detection, character strings, and dates and times. In short, a great course for experienced R users who are interested in learning new data management skills and tricks.

• College credits: NO — Certificate of Completion only
• Price: $9.99 on sale ($109.99 regular price)
• Financial aid or scholarships: NO
• Mobile learning: YES
• Self-paced learning: YES
• Flexible deadlines: YES
• Time needed for completion: 6 hours
• Languages: English with subtitles in English
• Vendor: Udemy

For more online courses, check TUN’s list of curated classes, or use the online classes search engine to find the best online courses in any subject.