Where to Find the Best Online R Courses, Classes, and Training

The R programming language is one of the most popular programming languages in the tech industry. It is most popular among data analysts and other data experts. However, R also has a wide range of applications beyond the world of data. 

This article will cover what R programming is, how it benefits tech experts, and where to find the best online R courses. If you’re interested in pursuing an online R programming course, it’s important to know your program preferences and needs so that you can filter your options accordingly. 

What Is R?

R is a software environment and programming language that is used primarily for statistical computing and graphics. R is an ideal alternative to modern statistical software packages like SAS and SPSS. This free open source language can be used across several operating systems, including Linux, Windows, UNIX, and macOS. 

Why Online R Courses Are Important for Professional Development

Enrolling in an online R course is an excellent way to pursue professional development because it allows you to add a new skill to your resume without the constraints that come with pursuing a university degree. Online R courses can help beginners enter the tech world, or they can lead to career advancement for current tech professionals. 

Should You Attend a Coding Bootcamp to Learn R?

Enrolling in a coding bootcamp is an excellent way to jumpstart your educational journey toward a career in data science. Since it is such a popular language, R is traditionally one of the core subjects taught in data science and data analytics bootcamps, so if you’re interested in learning R programming from scratch, a coding bootcamp would be especially helpful.

Overview: The Best Online R Courses, Classes, or Training

The table below shows the wide variety of high-quality courses, classes, and training programs available for learning R. They differ in terms of time commitment, price, and provider, all of which are important factors to consider when deciding which program is best suited for you.

Provider	Course	Price	Length	Certificate
Coursera	Mastering Software Development in R Specialization	$39 Per month	6 Months	Yes
Coursera	R Programming	$49 Per Month	57 Hours	Yes
Coursera	Statistics with R Specialization	$49 Per Month	7 Months	Yes
DataCamp	R Programming	$33 Per Month	22 Hours	No
Data Science Dojo	Beginning R Programming	Free	2 Hours	No
eCornell	Data Analytics in R	$3,600	3 Months	Yes
eCornell	Data Science Essentials	$3,600	2 Months	Yes
edX	Data Science: R Basics	$149	8 Weeks	Yes
General Assembly	Introduction to R	$35	2 Hours	No
NYC Data Science Academy	Data Science with R: Data Analysis and Visualization	$2,190	35 Hours	Yes
Simplilearn	Data Science with R Certification Course	$599 – $699	64 Hours	Yes
Udemy	Data Science and Machine Learning Bootcamp with R	$85	17 Hours, 45 Minutes	Yes
Udemy	R Programming A-Z: R for Data Science with Real Exercises	$85	10 Hours, 39 Minutes	Yes
Udemy	R Programming: Advanced Analytics in R for Data Science	$85	6 Hours	Yes
University of Washington	Certificate in Statistical Analysis with R Programming	$5,025	8 Months	Yes

In Detail: The Best Online R Classes, Courses, or Training

Mastering Software Development in R Specialization | Coursera 

• Learning Format: Series of five courses 
• Level: Beginner  
• Subjects Covered: R programming, GitHub, programming tools, functional programming, logic programming, regular expression (regex), data manipulation, object oriented programming, Tidyverse, ggplot2, data visualization

If you want to master R programming as a core part of software development instead of just data science, this specialization might be ideal for you. This specialization combines theory with hands-on learning and is facilitated by Coursera and offered by Johns Hopkins University. 

The five courses in this specialization are The R Programming Environment, Advanced R Programming, Building R Packages, Building Data Visualization Tools, and Mastering Software Development in R Capstone. This specialization includes graded quizzes, programming assignments, and shareable certificates of completion.

Key Takeaway: This in-depth specialization allows students to practice the skills they’re learning through hands-on projects, all of which can be added to a professional portfolio.

R Programming | Coursera 

• Learning Format: Full course 
• Level: Intermediate 
• Subjects Covered: History of R and S, programming with R, debugging, loop functions, data simulation with R

This intermediate-level R programming course is accessible on Coursera via Johns Hopkins University. It is divided into four sections, the entirety of which can be completed in four weeks or at your own pace. The course begins by providing background information on R before transitioning into more advanced material. 

Each section of the course has videos, articles, and interactive quizzes. Upon completing the course, students are awarded a shareable certificate. Coursera also offers an auditable version of this class, which allows students to follow along through course materials, but restricts access to any other resources.

Key Takeaway: This is an ideal course for intermediate learners who want to move beyond the basics of programming in R. It’s offered by Johns Hopkins University, which is a world-renowned institution. 

Statistics with R Specialization | Coursera 

• Learning Format: Series of five courses
• Level: Beginner 
• Subjects Covered: R programming basics, Bayesian statistics, linear regression, statistical inference, model selection, Bayesian approaches, Bayesian linear regression, regression analysis, statistical tests, exploratory and effective data analysis 

Coursera offers this beginner specialization in collaboration with Duke University. If students devote about three hours a week to the program, they will complete it within seven months. However, if you prefer to get through it more quickly, or you need more time, it’s flexible enough to allow students to complete it at their own pace.

The five courses in the specialization include Introduction to Probability and Data with R, Inferential Statistics, Linear Regression and Modeling, Bayesian Statistics, and Statistics with R Capstone. If you aren’t sure that you want to commit to the entire specialization, you can purchase a single course.

Key Takeaway: This five-course specialization is designed to fully prepare and qualify students for jobs in data analysis and statistical analysis.  

R Programming | DataCamp 

• Learning Format: Full course with hands-on training  
• Level: Beginner 
• Subjects Covered: Data structures, object oriented programming, data visualization, machine learning

This is a subscription-based course that’s ideal for anyone who wants to solely learn R programming. The program was designed by a variety of instructors and put together in order of ascending difficulty. So, even if it starts with an introduction to R, students complete the program with an in-depth grasp of the subject. 

There are currently five modules in the program, including Introduction to R, Intermediate R, Writing R Codes, Introduction to Writing Functions in R, and Object Oriented Programming. If you want to try out the course before paying for a subscription, you can access the first module for free, along with some of its resources.

Key Takeaway: DataCamp has designed this course to transform beginners into R programming experts. There are several subscription options available, including a free version that allows you to access the first module of any course before paying. 

Beginning R Programming | Data Science Dojo 

• Learning Format: Full course  
• Level: Beginner 
• Subjects Covered: Fundamentals of R, objects in R, functions, and control statements

Data Science Dojo is one of the best bootcamps for fast-paced intensive training, and it promotes a real-world approach to learning R programming. The two-hour course includes 11 videos that mainly focus on R data types, variables, vectors, lists, datasets, objects in R, and R operators. 

Upon completion, students will know the fundamentals of programming and will be able to create variables, read and write data in R, work with vectors, understand factors, call a function in R, and write a function. Data Science Dojo also provides programming tutorials that combine R and Python programming concepts. 

Key Takeaway: This course is provided for free and equips students with the fundamental data programming tools and knowledge required for entry-level positions. 

Data Analytics in R | eCornell 

• Learning Format: Instructor-led certificate program 
• Level: Intermediate 
• Subjects Covered: Prescriptive analytics in R, clustering, classification, machine learning

This is one of the many non-degree certificate programs offered by eCornell. Using R as your go-to programming language, you will learn how to manipulate data. Students are required to have experience in prescriptive and predictive data analytics, programming syntax, modeling Monte Carlo simulations, and familiarity with programming syntax. 

This program is instructor-led, meaning that the teaching is done through live lectures. You can expect to commit to five to eight hours of live learning per week. Upon completion, you’ll earn the Analytics in R Certificate from Cornell, in addition to 72 professional development hours and a variety of projects to add to your portfolio. 

Key Takeaway: This two-month program consists of four two-week classes and focuses on data analytics in R. Upon completing the program, you’ll earn the Analytics in R Certificate from an Ivy League school. 

Data Science Essentials | eCornell 

• Learning Format: Instructor-led certificate program 
• Level: Intermediate 
• Subjects Covered: R programming, Tidyverse, data visualization, predictive analysis, dynamic programming 

This is a data science program that takes a detailed approach to statistical programming with R. Each of the four courses takes two weeks to complete and will require five to eight hours of participation per week. Upon completion, you’ll earn the Data Science Essentials Certificate, along with 64 professional development hours and a data science project or two to add to your portfolio.

The course is divided into four parts, which must be completed in order. These sections are Exploring Data Sets with R, Summarizing and Visualizing Data, Measuring Relationships and Uncertainty, and Data Cleaning with the Tidyverse. 

Key Takeaway: This two-month program allows students to gain valuable knowledge and experience for a data science career. It’s most ideal for students who aspire to get jobs in data science, business, or market analysis. 

Data Science: R Basics | edX 

• Learning Format: Self-paced course
• Level: Beginner 
• Subjects Covered: R Programming, data visualization, data analysis, data science 

This course is offered by Harvard University in collaboration with edX. The program covers the basics of R syntax, indexing, vectors arithmetic, basic data types, data wrangling, plot making, and UNIX/Linux. Students can audit this course for free or pay the fee to have unlimited access to course content, take graded assignments and exams, and receive a shareable certificate.

To complete the course in eight weeks, you will only need to devote one to two hours per week to learning. The more hours a week you invest, the faster you’ll complete the program. Alternatively, if you have a busy schedule and need to get through the course more slowly than the recommended one to two hours, you can enjoy the self-paced benefit of this course. 

Key Takeaway: This course is designed and offered by Harvard University, which is one of the top universities in the world. Upon completing the course, you’ll receive a shareable certificate, which will help to enhance your resume. 

Introduction to R | General Assembly 

• Learning Format: Workshop with hands-on training 
• Level: Beginner   
• Subjects Covered: R syntax, SQL, data visualization 

This workshop is one of the many short and affordable tech classes offered by General Assembly. Anyone who wants foundational knowledge in R can enroll online irrespective of location. All you need to get started is Zoom and Slack, which you can easily download on your laptop or mobile device. 

By the end of the program, you should be able to manipulate and visualize data. After the workshop, if you want to develop a deeper understanding of R, you can enroll in the data science or data analytics program. 

Key Takeaway: Through this workshop, students can effectively and affordably learn the basic concepts of R. 

Data Science with R: Data Analysis and Visualization | NYC Data Science Academy

• Learning Format: Live course
• Level: Beginner  
• Subjects Covered: Data objects, RStudio, R packages, string manipulation, and data visualization

With basic knowledge of computer programming and components, you can enroll in this 35-hour course at NYC Data Science Academy. The program is divided into five modules or units, including Basic Programming with R, Basic Data Elements, Manipulating Data with dplyr, Data Graphics and Data Visualization, and Advanced Visualization. 

To qualify for the certificate of completion, you will need to attend at least 85 percent of all classes and complete 80 percent of the homework. There are different start dates available for this program, so you can choose the one most suitable for you. 

Key Takeaway: This thorough and comprehensive beginner course is designed to prepare students for the workplace. If you enroll in the data science bootcamp within nine months of completing this course, it will deduct the price of this course from your tuition cost.

Data Science with R Certification Course | Simplilearn  

• Learning Format: Full course with hands-on training
• Level: Beginner 
• Subjects Covered: R programming, business analytics, graphics for R in data visualization, common data structures, DBSCAN clustering, Apriori algorithm

This is a short but intense online course for R programming and closely related subjects. Some of the topics covered in this course are data exploration, predictive modeling, descriptive analysis, data visualization, data structures, forecasting, statistical concepts, and cluster analysis. 

Since it is a standalone course, you can take it without paying the heavy tuition fees for regular bootcamp courses. This course includes lifetime access to course content, 10 real-life industry projects, and 64 hours total of applied learning. Course participants can request a full refund within seven days if they aren’t satisfied. 

Key Takeaway: This course covers many general concepts of R programming. It includes 10 hands-on projects, which is especially beneficial to students who are working to build their professional portfolios.

Data Science and Machine Learning Bootcamp with R | Udemy

• Learning Format: Self-paced course with hands-on training 
• Level: Beginner 
• Subjects Covered: Introduction to R Basics, R Matrices, R Data Frames, R Lists, Data Input and Output with R, R Programming, and Machine Learning with R, 

Udemy offers this in-depth course that’s designed to significantly transform basic R skills into R expertise. The course includes almost 18 hours of material in the form of videos, articles, and downloadable resources. The course fee also gets you lifetime access to course content and a certificate of completion.

Upon completing the course, students will know how to program in R, how to create data visualizations, how to use R to manipulate data, and how to handle CSV, Excel, and SQL files or web pages. 

Key Takeaway: This intensive course is ideal for students without an R programming background who would like to quickly and effectively develop the necessary skills to begin a related career. 

R Programming A-Z: R for Data Science with Real Exercises | Udemy 

• Learning Format: Self-paced course with hands-on training 
• Level: Beginner 
• Subjects Covered: Fundamentals of R, RStudio, packages, basic R functions, ggplot2, data analytics, data science

As a beginner-level course, this program starts with an introduction to programming before jumping into R programming. You will learn almost everything there is to know about using R, from creating vectors to customizing RStudio. The course also covers advanced visualization. It includes 10-and-a-half hours of on-demand video, six articles, lifetime access, and a certificate of completion.

Key Takeaway: Over 200,000 students have enrolled in this bestselling R programming course. It is designed to equip students with everything they need before entering the workplace.

R Programming: Advanced Analytics in R for Data Science | Udemy 

• Learning Format: Self-paced course
• Level: Advanced 
• Subjects Covered: Data science, data analytics, advanced R programming, ggplot2, statistical analysis in business 

If you already have an R programming background that you want to take to the next level, this advanced-level course is for you. By the end of the program, you will know how to retrieve missing data, use R for data preparation, and create a time series plot in R. Its six hours of content also include lessons on the application of median imputation in data recovery.

This course includes six hours of on-demand video, five articles, lifetime access, and a certificate of completion. As this is an advanced course, students are required to have basic knowledge of R, data frames, vectors and vectorized operations, and the ggplot2 package.

Key Takeaway: This course is designed for advanced students who already possess general knowledge of R and have some programming experience. It’s ideal for anyone who already works in the field and wants to advance their career or acquire new skills.  

Certificate in Statistical Analysis with R Programming | University of Washington 

• Learning Format: Instructor-led certificate program
• Level: Advanced  
• Subjects Covered: R programming, data visualization, data plotting, complex data structures, linear modeling, and probability theory

This advanced online certificate program focuses on upscaling students’ R programming expertise. Classes are held in the evenings, and will cover a variety of topics, from how to carry out enterprise-scale data analysis using R to modern applied statistics. Be aware that this is a graduate certificate program, so participants must have a college degree to enroll. 

The program is divided into three parts, including Introduction to Statistical Analysis with R, Data Analysis and Modeling With R, and Advanced R Programming and Graphics. When you have completed the program, your certificate will be awarded by the UW Department of Statistics. 

Key Takeaway: This is a graduate certificate program, which requires students to have a bachelor’s degree and have work experience in the tech field. This program is ideal for anyone who doesn’t want to invest the time and money in a master’s degree program, but wishes to advance their R programming skills.

Online R Classes, Training, or Courses: Which Is the Right Option?

In education, courses, classes, and training are terms that often describe the same learning experience. However, they slightly differ. Classes are generally focused on one topic and are very short-term. On the other hand, courses and training programs cover a variety of related topics and practical issues in as little as several hours to as long as several months. 

How to Choose the Right Online R Course, Class, or Training Program

First Factor: Curriculum 

Before you enroll in an online R course, you should go through the syllabus to know what you’re investing in. For R, you want to make sure that subjects like generic programming language concepts, data handling, data manipulation, debugging, profiling of the R code, data wrangling, operating systems, and web scraping are included in the curriculum. 

For more advanced courses, subjects like machine learning, artificial intelligence models, the RStudio interface, SQL, Python programming, C++ in R, data parsing, and Java code in R should be included. The curriculum should correspond to your reasons for pursuing an online R programming course.

Second Factor: Hands-On Experience 

The best courses for R programming combine conceptual understanding with hands-on practice. For this reason, you want to compare different programs to see which ones give you the most opportunity for hands-on experience, especially on data science or data analysis projects that can be added to your professional portfolio. 

While some courses focus more on the theoretical side of R, others incorporate lots of practice to get students proficient in R programming. It’s really helpful to not only get hands-on experience but to have a way to prove it through real-life projects. This is especially important if you’re pursuing an online R programming course for professional development.

Third Factor: Certificate of Completion 

Certificates of completion are important because they prove that you obtained the knowledge and skills advertised in the course description. While certificates of completion typically only prove participation, they still authenticate skillsets and propel you to further your education. Most courses completed on Coursera, edX, and LinkedIn Learning offer a certificate.

If you’re enrolling in an online R programming course because of a professional or educational requirement, you’ll likely need to provide proof of having fulfilled the requirement, and generally, employers and educators will expect to see a certificate of completion.

R Course Certificates vs Certifications

Certificates and certifications are often mistaken for one another. However, they differ in significant ways. Certificates are earned by completing an associated program, and they serve as proof of completion. On the other hand, certifications are earned by passing an associated exam, and they serve as proof of eligibility in the associated field. 

Importance of R Certifications

R certifications are important for professional development because they help employers gauge your skillset during the hiring process. There are different levels of certifications and the most advanced ones typically pave the way for more job opportunities. Another benefit of professional R certifications is that they may increase your earning potential. 

Why You Should Take Online R Courses or Classes

Online R courses give you the knowledge you need to dive into the ever-evolving world of data. The United States Bureau of Labor Statistics estimates that jobs for statisticians and mathematicians will rise by 33 percent between 2020 and 2030. So, investing in learning R will quickly pay off. 

Online education saves you time and money, and it allows you to acquire key skills from the comfort of your home while meeting your current obligations. You do not need to get a four-year computer science degree or an online software engineering degree to have a successful programming journey.