Along with Python and Julia, R is among the leading programming languages for data science. It is an excellent option for graphics and statistical computing. Hence, learning R can benefit anyone interested in data science.
There are several ways to learn R. One of them is through courses. Here, we will discuss 10 top-rated R courses. However, before delving into that, let’s first know a little more about R.
What is R?
Contrary to what many people might think, R is not only a programming language. Instead, it is a platform for statistical analysis and graphics. Therefore, R programming language and R platform are two separate things.
Released in August of 1993, The R Project for Statistical Computing is a free platform developed by the R Core Team and the R Foundation for Statistical Computing.
10 Best R Courses To Learn in 2023
The following is a list of the 10 best R courses from leading course providers that assist you in learning R at your own pace:
1. R Programming
Highlights
- By: Coursera (and Johns Hopkins University)
- Level: Intermediate
- Duration: 57 hours
- Instructor: Brian Caffo, Jeff Leek, and Roger D. Peng
- Certificate: Yes
R Programming is an intermediate-level R certification courses program on Coursera that introduces learners to programming in R to carry out effective data analysis . It is a part of two Coursera specializations, namely Data Science Specialization and Data Science: Foundations Using R Specialization.
The course is excellent for learning how generic programming language concepts are implemented in a high-level statistical language like R. In addition to data analysis and R programming, candidates will gain Rstudio and debugging skills.
There are 3 instructors for the course- Brian Caffo, Jeff Leek, and Roger D. Peng. The trio has PhDs in Biostatics, and they work in the Bloomberg School of Public Health. Till date, the R course has been picked up by 654k+ learners and flaunts a 4.5 stars rating, averaging over 21.5k+ reviews.
Key highlights :
- The course (subtitles) is available in 12 languages in addition to English, including Arabic, Italian, Japanese, Korean, and Spanish.
- The course is replete with relevant exercises and quizzes.
You can sign up for the course here .
2. R Level 1 - Data Analytics with R
Highlights
- By: Udemy
- Level: Beginner
- Duration: 8 hours and 42 minutes
- Instructor: R-Tutorials Training
- Certificate: Yes
This is the best R course for beginners available on Udemy. As such, it introduces you to the R programming language and how R base can be used to develop many types of graphs. Moreover, it lays special emphasis on functions and loops in R.
The entire course is divided into 9 sections and 87 lectures. You need to have a basic understanding of data structure and statistics to get the most out of this R course.
It is among the top-rated R courses businesses like to have to train their employees. By the end of the course, you will be capable of creating and handling many types of objects. Moreover, you will receive a certification of completion that can help your resume to stand out for job interviews.
Key highlights :
- It is an ideal course for candidates interested in learning graph development in R.
- It offers full lifetime access.
- The course comes with 4 articles and 2 downloadable resources.
Sign up here to start learning the course.
3. Introduction to R
Highlights
- By: DataCamp
- Level: Beginner
- Duration: 4 hours
- Certificate: Yes
DataCamp is one of the top-rated places for online learning. It offers a galore of judicious courses on R. One of them is Introduction to R. This R course intends to allow learners to champion the concepts of data analysis by manipulating data frames, matrices, vectors, and other data structures.
At the time of writing, this course has been taken by over 2.2 million learners. The entire course is divided into 6 sections. To ensure comprehensive learning of the course, it comes with 62 exercises.
Introduction to R is a part of three tracks on DataCamp, namely Data Analyst, Data Science, and R Programming. Therefore, you can embark on these tracks if you want to be one of them.
Key highlights :
- It is a free R course.
- It is an ideal course to get started with data analysis using R.
- The course is prepared by Jonathan Cornelissen, who is the co-founder of DataCamp and the original author of a popular R package for quantitative finance.
You can sign up for the course here .
4. Data Science: Probability
Highlights
- By: Harvard University (in association with edX)
- Level: Beginner
- Duration: 8 weeks ( 1 to 2 hours/week)
- Instructor: Rafael Irizarry
- Certificate: Yes
Data Science: Probability is an ideal R course for beginners looking to learn data science, R, and probability. Offered by Harvard University, this course focuses on probability theory using a case study of the financial crisis of 2007-2008 .
This course on R programming and data science covers many topics. This includes performing Monte Carlo simulations, random variables and independence, how to compute expected values and standard errors in R, and the importance of the Central Limit Theorem.
The course is prepared by Rafael Irizarry, who is a Professor of Biostatistics at T.H. Chan School of Public Health. Data Science: Probability is a self-paced course that you can complete in 8 weeks by investing 1 to 2 hours a week.
The course is free to take; however, if you want a certificate of completion, then you need to pay $99, which is a nominal amount considering the value of this R course.
Key highlights :
- It is an ideal course for beginners.
- A free option is available.
To get started with the course, enroll here .
5. Learn R
Highlights
- By: codecademy
- Level: Intermediate
- Duration: 20 hours
- Certificate: Yes
Learn R by codecademy is another entry on our list of the finest R courses. The course introduces learners to the fundamental programming concepts in the R programming language. It details organizing, modifying, and cleaning data frames. The entire course is spread across 10 sections:
- Introduction
- Data Frames
- Data Cleaning
- Fundamentals of Data Visualization with ggplot2.
- Aggregates
- Joining Tables
- Mean, Median, and Mode
- Variance and Standard Deviation
- Quartiles, Quantiles, and Interquartile Range
- Hypothesis Testing
There are no coding prerequisites to enroll for this R programming course. However, having basic knowledge of data analysis and data science will be helpful. The course demonstrates creating data visualizations to detect insights in data in an excellent way.
To further enhance the learning experience, Learn R offers candidates to work on 3 portfolio projects, namely calculating population change, 1985 cars dataset exploration, and cleaning US census data. However, you need to avail Codecademy PRO to avail of this benefit. Candidates need to invest merely 20 hours to complete this course.
Key highlights :
- It is a free R course. However, to gain the certificate of completion, you need to use Codecademy PRO.
- Get access to Quizzes and videos from Codecademy PRO.
Get started with the course here .
6. RShiny for Everyone
Highlights
- By: edX (and DavidsonX)
- Level: Beginner
- Duration: 4 weeks (3 to 5 hours/week)
- Instructor: Owen Bezwick
- Certificate: Yes
If you want to learn web app development using R, then RShiny for Everyone is the go-to course. In case you don’t know, then let us tell you that Shiny is a popular R package that facilitates the development of interactive and data-driven web apps with the popular programming language for data science.
The course requires some prior experience with R and RStudio. With this online R course, you will learn:
- Creating maps, specific UI components, and visualizations.
- Storing data using the Google Sheets API.
- Structuring an application using shinydashboard.
To explain web app development using Shiny, the course involves learners developing a web app that showcases the biodiversity of America’s National Parks. The application will include specific components like a biodiversity calculator, interactive map, species images, and trail journal.
Key highlights :
- The course is free to take via Audit Track.
- It is an excellent course to learn to customize an application with CSS and deploy it via shinyapps.io.
You can enroll in the course here .
7. R Programming Full Course In 7 Hours
Highlights
- By: YouTube (and Simplilearn)
- Level: Beginner
- Duration: 7 hours
- Certificate: No
Simplilearn is one of the leading platforms for online learning. R Programming Full Course In 7 Hours is a YouTube video by Simplilearn that comprehensively covers the fundamentals of R programming. The course details many topics in in-depth, including:
- Variables and data types
- Logical operators
- Vectors
- List
- Matrix
- Data frame
- Flow control
- Functions in R
- Data manipulation
- Data visualization
- Time series analysis
The R course details two of the most popular packages in R, namely dplyr and tidyr. dplyr is one of the core packages of tidyverse (a collection of open-source packages) that help with data manipulation. For the same, it comes equipped with functions.
tidyr is an immensely useful R package that helps to clean data. It comes with three main functions to clean data, which are gather(), separate(), and spread().
Key highlights :
- It is a free R course.
- This course is ideal for learning data analysis.
There is no need to sign up for the course.
8. Introduction to Time Series Analysis and Forecasting in R
Highlights
- By: Udemy
- Level: Intermediate
- Duration: 8-and-a-half hours
- Instructor: R-Tutorials Training
- Certificate: Yes
This course is an intermediate-level R certification course offered by Udemy. It is among the bestseller R courses on the online learning platform, with an average rating of 4.4 stars out of 5.
The course introduces learners to using R for performing calculations with time- and date-based data. It also explains using models for data forecasting and converting standard data into time-series format. The course is prepared by R-Tutorials Training, which primarily provides data science courses.
You will also learn about the various popular time-series libraries. The entire course is divided into 8 sections and 74 lectures that you can go through as you please.
Key highlights :
- It compares the accuracy of different models to help you choose the best ones in different scenarios.
- The course is offered at a nominal fee and offers a certificate of completion.
To enroll in the course, you can click here .
9. Introduction to Probability and Data with R
Highlights
- By: Coursera (and Duke University)
- Level: Beginner
- Duration: 14 hours
- Instructor: Mine Çetinkaya-Rundel
- Certificate: Yes
It is a beginner-level course that introduces learners to sampling, exploring data, probability theory, and Bayes’ rule. This course explains the various sampling methods and their impact on the scope of inference.
Introduction to Probability and Data with R also explores one of the crucial aspects of data science, which is exploratory data analysis. It sheds light on the various techniques used for EDA, primarily on basic data visualization and numeric summary statistics.
The R course for beginners comes with a galore of exercises and a project. Mine Çetinkaya-Rundel is the instructor of the course who is an Associate Professor of the Practice in the Department of Statistical Science at Duke University.
Key highlights :
- It is available in 10 languages, including Arabic, French, Korean, and Vietnamese.
- The course comes with flexible deadlines.
- It is a 100% online course.
To get started with the course, register here .
10. Advanced Statistical Inference and Modelling Using R
Highlights
- By: edX
- Level: Intermediate
- Duration: 6 weeks (5 to 10 hours per week)
- Instructor: Elena MoltChanova
- Certificate: Yes (Verified Track)
If you have already covered the basics of R and are now looking for something more complex, you should opt for Advanced Statistical Inference and Modelling Using R. It is an excellent course to learn linear regression in detail.
When learners invest 5 to 10 hours on a weekly basis, this course can complete in around 6 weeks. Candidates need to have a basic understanding of linear regression and statistical inference to get the most out of this R course.
Learners have two ways to opt for the course, namely Audit Track and Verified Track. While the former is free to take, the latter comes with a certificate of completion and many other desirable features.
The R course is the second part of the Statistical Analysis in R Programming certificate. It is delivered by Elena Moltchanova, who is a Professor of Statistics at the University of Canterbury.
Key highlights :
- It details multivariate analysis using GLMs (Generalised Linear Models).
- It is a self-paced course.
You can enroll in the course here .
Conclusion
That sums up our list of the best R courses. Please note this is not an exclusive list of best R courses, and thus, there are many, many more great courses available on R programming. However, these are some of the best ones to choose from.
Also, you can consider reading the best R books to gain a thorough knowledge of the subject.
Do let us know via the comments section which of the courses mentioned above have helped you master R.
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