# best online course for r programming

Last Updated on August 8, 2022 by Team College Learners

If you love the power of R programming, but want to learn it from a step-by-step and guided perspective, then your best option is to buy an online course. While it’s true that you can learn ample material from books, e-books, and a variety of online resources, it might be a good idea to consider taking an online course if you’re looking for a more personalized approach. More importantly, an online course can provide the material in a fast and effective way.

What is R Programming Language?

R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. While R is widely used among statisticians and data miners for statistical software and data analysis, it is becoming popular among data scientists as well. Proficiency in R has become a standard requirement for many data science and statistician-related jobs.

Why learn R?

We recommend these courses for those with some basic knowledge of R that want to use it in a Data Science and Software Development context. You may wish to use it for exploratory data analysis, data visualization, probability, inference, linear regression, and more. You may desire to expand your data science skills and use R in your everyday role to interact more with the data you work with.

What jobs use R?

According to Burning Glass, there were ~50K job postings in the last 12 months requiring R as a skill. Some of the functional job titles requiring this skill are Business Intelligence Analyst, Operations Research Analyst, Management Analyst, and Market Research Analyst. If your work involves data analysis, modeling, or visualization, R is a powerful skill to add to your portfolio.

What skills or experience do I need to already have, before starting to learn R?While there are generally no specific prerequisites for beginner-level R courses, programming language basics is one of the key topics you typically need to know before you start to learn R programming language. It can also help if you have a solid understanding of math and statistics before beginning R courses. Introductory-level data visualization skills, such as understanding how plots and graphs work, can also be helpful when learning the R programming language. Additionally, analytical and critical thinking skills can be helpful when you’re starting to study R.

What kind of people are best suited for roles in R?

People who are highly analytical and curious are typically best suited for roles in R. People who enjoy statistics and using statistical models to solve problems can also be well suited to roles in R. Those who have an affinity for using computer technology and machine learning can potentially be well suited to learning this programming language. People who enjoy highly detailed tasks and who have strong problem-solving skills are typically well suited for R roles. Additionally, people who work in fields like lean manufacturing, public health, and finance can be well suited for roles in R.

What are common career paths for someone in R?

Some common career paths for people in R include machine learning engineers, data scientists, data miners, data engineers, and statisticians. These fall under the category of computer programming jobs, which according to the Bureau of Labor Statistics pay a higher than average wage. These types of computer programming jobs typically require a bachelor’s degree. Competition can be stiff for these jobs, though, due to the influx of workers in the field as a result of global trade.

What topics can I study that are related to R?

Mathematics, statistics, and AI are topics you could study that are related to R. Data visualization is another related topic, along with probability and the broader field of data science. You could study the related topics of data structure, data analysis, and data type as part of your R studies. Data manipulation and data cleansing are related topics that you could study, and you could also study GitHub and regular expression (REGEX).

## In summary, here are 10 of our most popular r courses

- Data Science: Foundations using R: Johns Hopkins University
- Statistics with R: Duke University
- Google Data Analytics: Google
- Data Analysis with R Programming: Google
- IBM Data Analytics with Excel and R: IBM
- R Programming: Johns Hopkins University
- Getting Started with R: Coursera Project Network
- Data Visualization & Dashboarding with R: Johns Hopkins University
- Applied Data Science with R: IBM
- Data Science: Johns Hopkins University

# Top 10 R Programming Certifications, Courses & Trainings Online in 2022

### Looking to learn R programming language? One of these R programming certification courses & classes will help you become an expert in programming in R.

- 1. R Programming Course A-Z™: R For Data Science With Real Exercises (Udemy)
- 2. Data Science and Machine Learning Bootcamp with R (Udemy)
- 3. R Programming Certification from Johns Hopkins University (Coursera)
- 4. Programming for Data Science with R Nanodegree Program (Udacity)
- 5. Data Science: R Basics Certificate by Harvard University (edX)
- 6. Statistics with R Certification by Duke University (Coursera)
- 7. R Programming: Advanced Analytics In R For Data Science (Udemy)
- 8. Mastering Software Development in R Certification by Johns Hopkins University (Coursera)
- 9. Learning R (LinkedIn Learning – Lynda)
- 10. R Programming for Statistics and Data Science (Udemy)
- 11. Statistics with R – Beginner Level (Udemy)

Data Science technologies have transformed the way analysts used to mine the data. R programming language is one such leading data science technology. According to 2017 Burtch Works Survey 40% of surveyed data scientists prefer R. It is undoubtedly the most popular language used by the data scientists around the world.

R is a software environment and a programming language that was specifically created for statistical computations and graphical applications. It has a gained a lot of traction since its inception, now becoming the leading tool for machine learning, data analysis & visualization and statistics. With major boom in big data, a lot of data science job opportunities are getting created every day and expertise in R programming will assist you in taking your career as data scientist to the next level.

When you search for R programming course or class, you will find a lot of resources. But there are a few good quality courses that are available for free. Our team of experts has handpicked best quality R programming certification, courses, classes, tutorials and trainings available online. This list includes both free and paid courses that can be taken by any beginner and expert level learners. These are not only applicable for learning Data Science and Machine Learning but equally useful for anybody learning R programming for use in graphical and statistical fields.

## 1. R Programming Course A-Z™: R For Data Science With Real Exercises (Udemy)

This is one of the best R programming tutorials that help you master programming in R and R studio with live examples. You will learn data analytics, data science, statistical analysis, packages, functions, GGPlot2.

More than 96,000 students have taken this Udemy R course. The course does not assume any prior knowledge or experience. It is designed in such a way that you can succeed at it even without any statistical background. It takes you step-by-step through the steep learning curve of R. You will be using specifically designed datasets to practice the skills you learn in the course.

The course begins with teaching R programming basics and how to combine programming and statistical concepts. Then the course progresses to advanced topics like matrices and data frames. All the course material is intertwined with ample of theory and real life examples to support learning. You will learn a new valuable skill in every single tutorial and in every section you will understand how you can apply that skill to solve real world problems.

**Key Highlights**

- Create visualizations to best capture your analysis and captivate your audience
- Learn to solve real life analytical challenges
- Learn how to customize R studio to suit your preferences
- Learn how to create and use vectors and matrices in R
- Learn how to install packages in R
- Practice working with financial, statistical and sports data in R
- Know all about Normal distribution and Law of Large Numbers
- Homework exercises for extra practice

**Duration : 10.5 hours on-demand video****Rating : 4.6****Sign up Here**

## 2. Data Science and Machine Learning Bootcamp with R (Udemy)

In this R language course you will learn how to program with R, how to use R for data analysis, how to create amazing data visualizations, and how to use Machine Learning with R. The course has been developed and is taught by Jose Portilla who is one of the best instructors on Udemy and has taught thousands of students about Data Science and Programming. The program is designed to be suitable for both experienced professionals who want to change career track to data science and complete beginners who wish to learn data science and machine learning from ground up.

This is a very comprehensive R course with over 100 HD video lectures, detailed code notebooks for every lecture, 8 articles and 3 downloadable resources. It takes you through environment setup to begin with and then the basics of programming in R along with vectors, matrices and data frames. Then it covers data visualizations in R leading to data Capstone project. Further, the course delves into machine learning with a dozen of portfolio projects. You get a certificate of completion on finishing the course.

**Key Highlights**

- Create Data Visualizations
- Use R to manipulate data easily
- Use R to handle csv, excel, SQL files or web scraping
- Learn machine learning algorithms including topics like Linear regression, Logistic regression and more advanced topics such as decision tress, random forests and support vector machines
- Variety of R programming exercises, capstone projects and Machine Learning portfolio projects
- Access to online Q&A forum
- Explore data mining of Twitter for tending topics and creating a word cloud of these topics

**Duration : 17.5 hours on-demand video****Rating : 4.6****Sign up Here**

## 3. R Programming Certification from Johns Hopkins University (Coursera)

This course is a part of Data Science Specialization from Johns Hopkins University. It is aimed at teaching R as a programming language and how to use R for effective data analysis. It covers practical issues in programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.

This Certification in R programming starts with basic building blocks of R like datatypes, functions to read and write data etc. Then it proceeds to formulate how to write R programs using control structures, R functions and basic operations on data. You will also learn about code profiling and debugging. The course also explores how to simulate data in R, which serves as the basis for doing simulation studies.

The course is instructed by Roger D. Peng, PhD, Associate Professor, Biostatistics; Jeff Leek, PhD, Associate Professor, Biostatistics and Brian Caffo, PhD Professor, Biostatistics.

**Key Highlights**

- Learn how to install and configure software necessary for a statistical programming environment
- Cover the history of R and S
- Learn to collect detailed information using R profiler
- Understand programming language concepts and their implementation in R
- Make use of R loop functions and debugging tools
- Comes from highly reputed university and highly acclaimed professors

**Duration : Approx. 20 hours****Rating : 4.6****Sign up Here**

## 4. Programming for Data Science with R Nanodegree Program (Udacity)

This Nanodegree program prepares learners for a career in Data science by teaching them the fundamental data programming tools of R, SQL, command line and git. The is an introductory program and is structured as a series of 3 courses – Introduction to SQL, Introduction to R Programming and Introduction to Version Control. During the course of the program, learners complete three projects, with a focus on the R language.

In the module on R programming, you will start by understanding common use cases of R and why it’s popular along with installation & setup of R Environment. You will learn to represent and store data using R data types and variables, and use conditionals and loops to control the flow of programs. You’ll also learn about complex data structures like lists to store collections of related data. Additionally you’ll learn to write your own custom functions, write scripts, and handle errors. Data visualization using R libraries is also covered in depth.

**Key Highlights**

- Learn the most important programming languages (R and SQL) used by the data scientists
- Learn to make beautiful visualizations using the ggplot2 library
- Use the popular diamonds dataset to put your R skills to work
- Industry relevant projects to gain hands-on experience
- Personalized feedback on projects from network of 900+ project reviewers
- Get access to student hub to connect with fellow learners
- Get access to technical mentor support and career support services
- No prior experience requirement to enrol for the program

**Duration : 3 months, 10 hours per week****Rating : 4.5****Sign up Here**

## 5. Data Science: R Basics Certificate by Harvard University (edX)

This is the first course in the 9-part Data Science professional certificate program offered by HarvardX on the edX platform. The goal of this edX R course is to introduce learners to the basics of R programming. This course has no prerequisites so it is suitable for anybody making a start in Data Science field. It is equally useful for anyone who has programming experience in another language, but would like to learn R programming.

This R programming certification course uses a real-world dataset about Crime in the United States to teach how to solve real problems using R. It covers R’s functions and data types, vector operations and advanced functions like sorting. You’ll learn how to apply general programming features like conditional construct “if-else,” and “for loop” commands, and how to wrangle, analyze and visualize data.

The course instructor Rafael Irizarry does a great job explaining topics in plain language making even complex topics very easy to understand. There are several programming assignments to solidify the learning. The course is available for free but you need to pay a small fee for graded exams and certificate of completion of course.

**Key Highlights**

- Build a strong foundation to prepare for more in-depth courses
- Learn data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux, version control with git and GitHub and reproducible document preparation with RStudio
- Learn to perform operations in R including sorting and making plots
- Learn to solve problems using real life dataset

**Duration : 8 weeks, 1 to 2 hours per week****Rating : 4.6****Sign up Here**

## 6. Statistics with R Certification by Duke University (Coursera)

Statistics with R certification is one of the best courses to master statistics with R. You will learn to analyze and visualize data in R and create reproducible data analysis reports.

This R statistics specialization includes 5 courses – Introduction to Probability and Data, Inferential Statistics, Linear Regression and Modeling, Bayesian Statistics and Statistics with R Capstone. The capstone project will be an analysis using R that answers a specific scientific/business question provided by the course team. The dataset for analysis will be provided to learners and they will need to apply various methods and techniques learnt in the previous courses.

Dr. Mine Çetinkaya-Rundel is the main instructor of the program along with three other Professors from the Duke University’s Department of Statistical Science. No programming experience is needed to take this program, just knowledge of basic maths and a genuine interest in data analysis.

**Key Highlights**

- Gain statistical mastery of data analysis including inference, modelling and Bayesian approaches
- Learn to wrangle and visualize data with R packages for data analysis
- Understand simple and multiple linear regression models
- Perform frequentist and Bayesian statistical inference and modeling to make data-based decisions
- Gain expertise needed to apply for statistical analysis or data scientist positions
- Plenty of practice exercises and tests
- Access to forum with great help to solve doubts

**Duration : Approx. 7 months, 4 hours per week****Rating : 4.7****Sign up Here**

## 7. R Programming: Advanced Analytics In R For Data Science (Udemy)

If you have basic knowledge of R programming language and want to take your skills to the next level, then this is the best R programming course for you. It focuses on data science & analytics and statistical analysis in R language. The instructor Kirill Eremenko takes you through the complex concepts in quite simplified and easy to understand manner.

The course consists of 51 lectures that cover Data preparation, Lists in R and “Apply” family of functions in detail. You will learn how to prepare data for analysis in R, perform median imputation method, work with date-times in R, how to use lists in R, how to use apply functions instead of loops, how to nest user defined functions with apply-type functions etc.

This course is not for complete beginners, and assumes basic knowledge of R. Knowledge of GGPlot2 package, dataframes, vectors and vectorized operations is also recommended.

**Key Highlights**

- Advanced level course for those who want to dive deep in R
- Professional R Video training
- Unique datasets designed with years of industry experience in mind
- Learn to create a timeseries plot in R
- Understand how the Apply family of functions works
- Locate missing data in your dataframes
- Learn to apply Factual Analysis method, Median Imputation method to replace missing records
- Engaging exercises to help correlate analytics in the real world

**Duration : 6 hours on-demand video****Rating : 4.7****Sign up Here**

## 8. Mastering Software Development in R Certification by Johns Hopkins University (Coursera)

This specialization in R programming provides rigorous training in R language and also teaches the best software development practices for building data science tools that are not only robust, modular and reusable but also collaborative (thus suitable for use in team based and community environments). Through this program you will gain necessary skills for handling complex data, building R packages and developing custom data visualizations.

This R language certification program comprises of 5 courses. It starts with an introduction to R (essential foundational concepts of R) and then moves on to advanced topics like functional programming, object-oriented programming, error-handling, user-functions, R packages and software maintenance. It ends with a Capstone project in R programming. You will find that throughout the program, the focus is on aspects of R language that are useful for creating tools and code that can be used by others.

The course assumes some programming experience (in any language) and working knowledge of mathematics up to algebra.

**Key Highlights**

- Gain fluency at the R console
- Be able to create tidy datasets from a wide range of possible data sources
- Learn to define new data types in R and develop a universe of functionality specific to those data types
- Learn how to distribute packages via CRAN and GitHub
- Create new visualization building blocks using the ggplot2 framework

**Duration : Flexible****Rating : 4.4****Sign up Here**

## 9. Learning R (LinkedIn Learning – Lynda)

This is a beginner level course that introduces you to the R programming language. It starts with instructions on installation of R, setting up the R environment and using R Studio. Then it proceeds to cover how to read data from spreadsheets & SPSS, how to use and manage packages for advanced R functions.

The instructor of this course is Barton Poulson who is a professor, designer and data analytics expert. He effectively takes you through several examples on how to create charts and plots, check statistical assumptions and the reliability of your data, look for data outliers, and use other data analysis tools.

**Key Highlights**

- Learn to use charts, such as histograms, bar charts, scatter plots, and box plots, to get the big picture of your data
- Learn descriptive statistics such as means, standard deviations, and correlations for a more precise depiction
- Learn inferential statistics like regression, t-tests, the analysis of variance, and the chi-square test to determine the reliability of your results
- Learn to create beautiful presentation charts to share your analysis results
- Several engaging exercises available with data sets which can be downloaded
- View Offline mode allows learners to download courses on mobile devices and watch them on the go without an internet connection

**Duration : 2 hours 25 minutes****Rating : 4.6****Sign up Here**

## 10. R Programming for Statistics and Data Science (Udemy)

This R Certification program is the most comprehensive introduction to R programming for Statistics and Data Science. The aim of this course is to progress you from being a complete beginner in R language to an expert professional who can take up data manipulation on demand. You will be exposed to fundamentals of programming, data manipulation techniques and tools, and data visualizations and plots. It also includes a step-by-step guide to statistics.

This R programming class is a very good blend of theory and practice. It takes care to incrementally build your theoretical knowledge and practical skills. Multiple exercises included in the course help to reinforce your learning. It also includes homework and projects to further challenge the learners. On completion of the course, you will receive a verifiable certificate.

**Key Highlights**

- Learn descriptive statistics and fundamentals of inferential statistics
- Master confidence intervals and hypothesis testing, as well as regression and cluster analysis
- Learn to work with vectors, matrices, data frames, and lists
- Become adept in ‘the Tidyverse package’ enabling you to index and subset data
- Learn the grammar of graphics and the ggplot2 package
- Learn how to visualise data – plot different types of data & draw insights
- Learn complete skill set to tackle a new Data Science project
- Learn to make decisions that are supported by the data

**Duration : 6.5 hours on-demand video****Rating : 4.5****Sign up Here**

## 11. Statistics with R – Beginner Level (Udemy)

This course on Udemy focuses on basic statistical analyses using R programming language. You will learn how to manipulate data in R and prepare it for the analysis – filtering your data frame, recoding variables and computing new variables. Also learn about computing the main statistical figures in R – mean, median, standard deviation, skewness, kurtosis etc., and data visualization using tables and charts.

The course includes 3 hours on-demand video, 13 articles and 12 downloadable resources and comes with full lifetime access. Though this is a brief course, it covers essential concepts thoroughly with examples for illustration. Large variety of data frames are provided for practice, along with notes and R files. This is a beginner level course and assumes knowledge of basic statistics.

**Key Highlights**

- Learn to Build frequency tables and cross tables
- Learn to Create histograms and cumulative frequency charts
- Learn to Build column charts, mean plot charts, boxplot charts and scatterplot charts
- Get statistical indicators by subgroups of the population
- Learn how to check for normality and for the presence of outliers
- Learn to determine skewness and kurtosis
- Learn to perform one-sample t test, the binomial test and the chi-square test for goodness-of-fit

**Duration : 3 hours on-demand video****Rating : 4.2****Sign up Here**

# 14 Best R Courses Online – 2022 Guide

**By** Aatisa | **Updated:** January 10, 2022 | **Reading Time:** 13 minutes |

### The best R Courses online for careers in finance, AI & analytics

*R *has recently surfaced as one of the most widely used open-source programming languages. With over two million R users worldwide, the language has cemented its spot in the fields of data science and statistics. What’s fascinating is that this number of *R* users grows by 40% every year.

The language’s popularity is beginning to mobilize aspiring programmers towards finding the perfect learner’s platform to master it*.* To help you make the right choice, we’ve come up with a concise but succinct list of the best *R* courses online that can catapult you into the professional league.

*R* Courses Online – Overview

As a programming language, *R* specifically caters to statistical computing and graphics. It is similar to *S* and much of its code runs unaltered under *R*. Since it provides a curated environment for statistical and graphical computing, users have complete control over its integrated suite of software for data manipulation, visualization, and mathematical plots.

*R*’s most applicable domains range from analytics-driven organizations such as Google and Facebook to finance and marketing. At intermediate and more advanced levels, *R* programmers leverage its flexibility in graphical and statistical techniques and in-built libraries for complex data manipulation.

Such high-end data-visualization is of extreme value in the fields of Retail, Manufacturing, BioScience, Healthcare, Sports, and more. The upcoming list of best *R *courses online will hopefully facilitate novice learners in making more informed decisions about the online *R* courses that align best with their learning curve.

### Best *R* Courses Online 2022 – Top Picks

R Programmer | Data Science with R | Data Visualization R |
---|---|---|

DataCamp | Udacity | Pluralsight |

Career Track | Nanodegree | Career Track |

from $25/month. Trial. | from $349/month. | from $29/month. Trial. |

★★★★☆ | ★★★★★ | ★★★★☆ |

Visit Website | Visit Website | Visit Website |

**Disclaimer: This post contains affiliate links. Read the full disclosure at the end of this post.*

Online courses around *R *language are curated to meet varying levels of expertise: beginner, intermediate, and advanced. Here are some of the best R courses online to choose from. This list does not claim to be comprehensive.**Contents**Show

*R* Courses Online – Best Individual Classes

### 1. Introduction to *R*, DataCamp

DataCamp offers a beginner’s *R* course (visit website) for aspiring data analysts. The class focuses on helping learners master factors, lists, and data frames. From introducing data types in *R *and assigning variables, modules gradually upgrade more complex functions.

Later modules focus on vectorization, working with matrices, factoring with subsets, creating data frames, and finally listing.

What makes DataCamp’s introductory *R* course a preferable choice for new learners is its hands-on approach towards data from real-world cases. For example, the second module takes learners on a trip to Vegas to factorize gambling results.

To make matrices more appreciable, the course analyzes box office numbers for the Star Wars series. Such implementation allows greater retention and practice opportunities for novice learners. This is one of the best R courses online to gain a quick overview of the basic concepts. You can test the platform with their free one-month trial offer.

**Instructor:** Jonathan Cornelissen | **Level:** Beginner | **Duration:** 4 hours | **Modules:** 6**Exercises:** 62 | **Pricing:** Standard Plan for $25/month. Premium: $35/month.**Info:** View Course. Get discount. Browse the full catalog of R Courses online.

### 2. *R* Programming A-Z, Udemy

Rated at 4.6/5, Udemy’s course R programming A-Z (visit website) can be studied in English, French, German, and 6 more languages via auto-translations.

Curated for its *Udemy for Business* collection, the course claims to train learners step-wise in successfully mastering the language. Without the need for any prior experience in programming, learners with varying skill levels are encouraged to apply.

Udemy’s content is packed with real-life challenges, some of which are solved together while others are assigned as homework exercises. Course content includes programming principles, basics in R, matrices, data frames, and advanced visualization with GGPlot2.

Learners will have the advantage of building on previously learned concepts before embarking on more complex functions. Starting at $11.99, this is among the best R courses online for beginners who don’t want to spend a fortune at the beginning. It can be bought in bulk with two other related courses: *Data Science and Machine learning Bootcamp with R*and *R Programming: Advanced Analytics in R for Data Science.*

**Instructor:** Kirill Eremenko | **Level:** Beginners | **Lectures:** 82**Video:** 10.5 hours | **User Rating:** 4.6/5 ★★★★☆**Price:** View course. From $11.99. Up to 95% off. Browse full catalog with R courses.

### 3. Programming with *R*, Pluralsight

Rated 4 out of 5 stars, Pluralsight’s introductory *R* course (visit website) is aimed at beginners looking for an entry-level career in data analytics with zero prior knowledge. Comprising of six modules, the class begins with a simple introduction to what makes *R* a preferred language in Data Science and Analytics.

Later modules include manipulating vectors, matrices, data frames, and managing control statements. However, you will begin by acquainting yourselves with the language’s syntax. Next comes data exploration and the different structures presented in R.

With sufficient knowledge in the backdrop, you will finally implement control statements to write your own functions. Coming out of the course, you will have achieved a foundational working knowledge of *R *to help the onset of an entry-level career in data analytics.

Priced at an affordable $19 billed annually, the class offers a ten-day free trial to help learners get a feel for its content. One of the best *R* courses online for beginners.

**Instructors:** Mihaeli Danci | **Skill Level:** Beginner**Info:** View course. $29/month. $299/year. | Get Free 7-day Trial.

### 4. R Programming – Advanced Analytics, Udemy

With around 50,000 enrolments, *R Programming* (visit website) is another one of Udemy’s bestsellers aimed at learners with a more intermediate skillset.

Since it involves advanced analytics, the course is a step ahead of the introductory program described earlier. Before enrolling, learners are required to possess a basic working knowledge of *R*, vectorization, GGPlot2 package, and data frames. You will come out of the course proficient at Data Science and Analytics with *R*?

Included in the program are lectures and exercises on data preparation (data filters, data frame index, and replacing data via median imputation methods) listing in *R* and the application of a suite of functions. This online R course can be bought in bulk with an introductory programming course and a curated Machine Learning boot camp.

**Instructor:** Kirill Eremenko | **Level:** Beginners | **Lectures:** 53**Video:** 6 hours | **User Rating:** 4.7/5 ★★★★☆**Price:** View course on Udemy. From $11.99. Up to 95% off. Browse all classes.

### 5. Learn R, Codecademy

Codecademy’s *Learn R* is a beginner course aimed at learners without any prior affiliation with programming. It’s a ten-module program that grants learners a certificate of completion towards the end.

Upon enrolling, learners will come away with skills in basic programming, organizing and modifying data frames, and data visualization that displays valuable insights. Lastly, you will be exposed to statistics and hypothesis testing to gain entry-level proficiency.

Codecademy’s pro plans are billed at $15 annually. It includes additional practice material to develop sizeable proficiency amongst novice learners. The platform offers eligible college students a special 38% discount upon subscription, without affecting the number of available course features.

**Certificate:** Yes | **Level**: Beginner | **Lessons:** 10 | **Completion Time:** 20 hours

### 6. Introduction to *R*, FutureLearn

Rated at 4.4 out of 5 stars, FutureLearn’s 4-week course is designed by Purdue University and puts learners abreast of airline data to master the fundamentals of *R*.

Here is an opportunity to implement the tools in *R* for analyzing big data. By applying for this course, learners will come out prepared for more complex level programs in *R* and an improved ability to implement data analytics.

FutureLearn aims this R course at beginners without the advantage of prior coding experience. *Introduction to R* will bring you abreast of important programming functions, including importing data into *R*, vectorized functions, data manipulation, and predictive analytics. Learners can also sign up for the weekly newsletter for updates.

**Provider:** Purdue University | **Certificate:** Yes | **Level**: Beginner | **Lectures:** 4**Complete in:** 4 weeks. 4hrs/week |** Course Rating:** 4.4/5

### 7. Statistics and R, HarvardX

HarvardX’s self-paced course on Statistics and *R* language offers a flexible 4 weeks of learning for fresh programmers with an intermediate skillset. Enrolment is open from March through October. Since it is an intermediate-level program, you will be expected to have prior familiarity with basic programming and Math.

Upon enrolling, you must brace yourself for *R* implementation and statistical data analysis in the life sciences environment. Core topics include random variables, distributions, p-values and confidence intervals, data exploration, and non-parametric statistics. You can also opt for an associated professional certificate in Data Analysis for Life Science.

HarvardX has divided its course into a series of seven parts. Depending on your prior experience with programming, you can opt for either the entire series or only the relevant courses. Statisticians with intermediate skills may skip the introductory R courses. As a learning tool, *Statistics and R *is a free course. A verified certificate will cost you $249.

**Category:** Statistics | **University:** HarvardX | **Level:** Intermediates**Students:** >340,000 | **Length:** 4 Weeks | **Efforts:** 3-5 hours/week

**Reading tips:** To explore more career and skills tracks in technology, browse our lists of best DataCamp courses, Udacity nanodegrees, and Pluralsight classes.

*R* Courses Online – Best Career Tracks

### 8. *R* Programmer – DataCamp

DataCamp offers an R career track (visit website) comprising of fourteen R courses online aimed at complete beginners looking to initiate a career in data analytics. These modules span over 48 hours of dedicated learning. It finishes off with three core projects and other hands-on exercises to help candidates learn and master *R*.

Since the track is aimed at complete beginners, no prior experience with *R* or coding is required. *R Programmer* trains learners in writing efficient codes, manipulating data, and managing complex data using APIs. The complexity of data can range from web information, text-based data, time, and dates.

Advanced modules then build upon prior skills. As you begin learning the ropes of *R *fundamentals, the modules advance to tougher concepts related to writing functions and object-oriented programming.

You’ll also be introduced to dominant *R* libraries including devtools, testthat, and rvest. These are crucial tools that help you with web development, analysis, and task automation. This curated path contains some of the best R courses online if you eye a career in technical analysis. Students can make use of one month’s free trial.

**Instructors:** David Robinson, Rasmus Bååth, Colin Gillespie, and others.**Duration:** 48 hours | **R Courses:** 14 | **Pricing:** from $25/month/annually.**Info:** View course. Try all courses 7-days free. Browse full catalog.

### 9. Programming for Data Science with *R*, Udacity

Udacity’s *Programming for Data Science with R* (visit website) is the result of a joint venture with Mode, a collaborative data science platform for SQL, Python, *R*, and visual analytics. This has helped Udacity’s career track incorporate more than one data analytic tool for learners’ proficiency. Upon enrolling, learners must brace themselves for around 3 months of learning given a 10hrs/week study plan.

Although this *R* nanodegree is aimed at beginners, Udacity still encourages aspiring *R* programmers to visit its nanodegree program in data analytics for easier accessibility to complex concepts. *Programming with R* begins with an introductory module on SQL and eventually moves towards *R* programming and version control for data sharing.

Udacity offers learners additional privileges that include, but aren’t limited to, hands-on projects based on real-world cases, career access via resume support, and uninterrupted technical mentorship. Rated at 4.85 out of 5 stars, this is among the best *R* courses online. You can get up to 75% off. Financial support is available.

**Instructors:** Josh Bernard, Derek Steer | **Duration:** 4 months. 10 hours/week**Level:** Beginners, Intermediates | **Prerequisites:** None.**Website: **View Course. Get up to 75% off. | **User Rating:** 4.7/5

### 10. Data Scientist with *R* – DataCamp

This DataCamp *R* career track (visit website) is directed at novice learners without prior coding experience. In contrast with its earlier program, *Data Scientist with R* is an extensive path spanning over 21 modules of dedicated learning. Opting for this track would require thorough commitment and a passionate fervor for mastering new skills.

*Data Scientist with R* is aimed at apprising novice data professionals with R’s versatility at manipulating, importing, cleaning, and visualizing complex data. Research-packed exercises allow learners to get hands-on with some integral skills and important packages within *R*. This includes ggplot2 and tidyverse packages such as dplyr and readr.

Later modules focus on teaching machine-learning and statistical techniques to enable learners to write their own functions and execute cluster analysis.

All in all, it’s a heavily loaded career track that will equip you with the credentials needed for a successful switch to being an entry-level data analyst. Again, before jumping to a subscription, learners have the choice to make use of the free trial to test the platform.

**Instructors:** Jonathan Cornelissen, David Robinson, and others**Duration:** 88 hours | **R Courses:** 22 | **Pricing:** from $25/month/annually.**Info:** View course. Try all courses 7-days free. Browse full catalog.

### 11. Data Visualization with R, Pluralsight

Pluralsight’s learning path (visit website.) makes use of visualization as a powerful tool to sum up millions of data points in one go. Learners of varying skill levels can apply for the track that extends from beginner-level modules all the way to advance. However, students should be familiar with data literacy and *R* for data analysts before enrolling.

You may opt for a particular module depending on your skillset or choose to take up the entire track. The availability of a skill measuring test can help make an informed decision around the right level to start at.

The introductory *R* courses include *R* graphics and visualization using ggplot2. From here the modules shift to purpose-based customization of visualized data and finally creating special purpose plots via *R* packages. You can start with a free trial.

**Instructors:** Emilee McWilliams, Martin Burger, Chase DeHan**Skill Level:** Beginner to Advanced | **R Courses Online:** 5**Info:** View course. $29/month. $299/year. | Get Free 7-day Trial.

### 12. Machine Learning Scientist with R – DataCamp

DataCamp’s Machine Learning Scientist (visit website) is aimed at programmers with a more intermediate skillset. With its introduction to advanced *R* programming, the career track claims to help programmers in securing a spot as data scientists. Spanning over 15 *R* courses, the career track requires roughly around 66 hours of dedicated learning.

As a data scientist in the making, you’ll be faced with both supervised and unsupervised learning. Using the various tools at your disposal, you will learn how to process data for modeling, train and visualize these models, and finally, assess and tune modeling parameters for better performance. Some new tools and techniques, such as Bayesian statistics, Spark, and natural language processing, will help you augment your skillset.

**Instructors:** Brett Lantz, John Mount, Nina Zumel, Hank Roark**Duration:** 61 hours | **R Courses:** 15 | **Pricing:** from $25/month/annually.**Info:** View course. Try all courses 7-days free. Browse full catalog.

### 13. Data Science: Foundations Using R, Coursera

Authorized by John Hopkins University, *Foundations Using R* is a curated specialization that spans over five R courses and takes approximately five months to complete.

Aimed at beginners, the specialization does not ask for any pre-requisite and works with a customizable pace gauge. Upon completion, learners can earn a sharable certificate to display on their online profiles and resume.

The initial modules focus on using* R* to clean, analyze and visualize data. From there, the content will shift to setting up *R, R* studio, and Github. Key skills involve exploratory data analysis, *R* programming, Regular Expression (REGEX), data manipulation, cluster analysis, and cleansing.

According to the claims on the website, the specialization has already catapulted around 38% of the applicants into switching careers and around 15% earned promotions. The specialization costs $49/month. Coursera offers financial aid to eligible candidates.

**From:** Johns Hopkins University | **Instructors:** Jeff Leek, PhD**For:** Beginners | **Duration:** 5 months | **R Courses**: 5 | **Verdict:** 4.6/5**Price:** Try 7 days free. From $44/month. View specialization.

### 14. Analyze Data with R, Codecademy

Codecademy’s skill path is aimed at beginners without prior skills in *R* programming or data analytics. Spanning over seven *R* courses, the online program allows novices to earn a certificate upon successful completion.

*Analyze Data with R* focuses on data visualization, data cleaning, statistical analysis, and regression. Through dedicated practice, learners will be able to master basic programming skills in *R*, explore popular libraries (ggplot2) and some more obscure ones, dip their toes in machine learning, and generate data reports.

Three heavy-duty projects will allow you to go hands-on with real-world data and upskill. Since it is a career track, Codecademy claims to provide step-wise guidance that builds on as you progress with the track. A free trial can help you decide if these *R* courses online are the right fit for you, in which case you’ll be charged $15 billed annually.

**Type:** Skill Path | **Certificate:** Yes | **Level**: Beginner | **Lectures:** 7**Completion Time:** 8 weeks |** Course Rating:** 4.8/5

## How to Choose the Best R Courses Online

With the smorgasbord of classes, skill tracks, and specializations available, choosing the best R courses online can be overwhelming. As with any online course, your decision must primarily begin with analyzing your skillset. Ask yourself the following questions:

- What’s your programming expertise in
*R*(or if you have one)? - What do you hope to attain after completing
*R*courses online? (Are you looking to upskill for an advanced-level course, or hoping to gain something career-wise?) - What’s your motivation level to take specific
*R*courses online? - What are your financial circumstances?

Your choice for a particular online *R* course will fluctuate based on how you answer the questions posited above. Remember that learning a programming language can be a strenuous process and beginners are known for dropping off in droves over the cliff of difficult syntax. Working on projects for a hands-on learning experience helps, and so does building up your motivation. To accomplish the latter, you can start with

- Identifying the data type you are interested in, and
- Identifying the kinds of project you see yourself doing in the future

Lastly, your choice for a particular *R* course or track must be informed by your financial situation as well as goals for the future. We also recommend looking into our curated lists of Python courses and Data Analytics courses to explore similar career and skill tracks.

## Best *R* Courses Online 2022 – Review Verdict

Wrapping up our review of the best *R* courses online. With the field of data analytics burning hotter than ever, mastering the *R* programming language can be a valuable addition to your skillset. Given the vast array of curated *R* courses online, the decision will come to rest on the available resources and learning exigencies.

Economical individual *R* courses, such as the ones offered by Pluralsight and DataCamp, would be best suited for beginners or learners with intermediate skillsets. More advanced learners can opt for career tracks and specializations.

It would be wisest to subscribe to *R *courses online or skill tracks that perfectly bridge your current qualifications with your future goals.

### Best R Courses Online 2022

**R Courses Online – Best Individual Classes**

- Introduction to R, DataCamp
- Programming with R, Pluralsight
- R Programming A-Z, Udemy
- R Programming – Advanced Analytics, Udemy
- Learn R, Codecademy
- Introduction to R, FutureLearn
- Statistics and R, HarvardX

**R Courses Online – Best Career Tracks**

- R Programmer – DataCamp
- Programming for Data Science with R, Udacity
- Data Scientist with R – DataCamp
- Data Visualization with R, Pluralsight
- Analyze Data with R, Codecademy
- Machine Learning Scientist with R – DataCamp
- Data Science: Foundations Using R, Coursera

What are the best *R* courses online? What is your learning experience? What could providers do to improve the usability of courses? Let us know in the comments below.

Sources: R Data Structures – 1 | Hash Tables – 2 | Hash Functions – 3