The 12 Best R Courses and Online Training to Consider for 2021

The Best R Courses and Online Training to Consider

The editors at Solutions Review have compiled this list of the best R courses and online training to consider for 2021.

R is a language and environment for statistical computing and graphics. R can be considered as a different implementation of S, and while there are some important differences, much of the code written for S runs unaltered on R. The language provides a variety of statistical and graphical techniques including linear and nonlinear modeling, classical statistical tests, time-series analysis, and classification and clustering. R capabilities are enhanced via user-created packages that allow for special statistical techniques, graphical devices and reporting.

With this in mind, we’ve compiled this list of the best R courses and online training to consider if you’re looking to grow your data science programming skills for work or career advancement. This is not an exhaustive list, but one that features the best R courses from trusted online platforms. We made sure to mention and link to related courses on each platform that may be worth exploring as well. Click GO TO TRAINING to learn more and register.

Note: The best R courses and training modules are listed alphabetically by online learning platform name.

Learn R

Platform: Codecademy

Description: Part of the Analyze Data with R skill path, this course will expose you to fundamental programming concepts in R. After the basics, you’ll learn how to organize, modify and clean data frames, a useful data structure in R. Then you’ll learn how to create data visualizations to showcase insights in data! Finish up with statistics and hypothesis testing to become a data analysis expert. You do not need to know how to code to enroll in this course.

Related path/track: Learn Statistics with R

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R Programming (Johns Hopkins University)

Platform: Coursera

Description: In this course, you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which include programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting on R code. Topics in statistical data analysis will provide working examples.

Related path/track: Introduction to Probability and Data with R (Duke University)

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Introduction to R

Platform: DataCamp

Description: Part of DataCamp’s robust R course directory, this module will enable you to master the basics of this widely used open-source language, including factors, lists, and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis. Oracle estimated over 2 million R users worldwide in 2012, cementing R as a leading programming language in statistics and data science.

Related paths/tracks: Intermediate R, Exploratory Data Analysis in R

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Data Science Certification Course using R

Platform: Edureka

Description: Edureka’s Data Science Training lets you gain expertise in machine learning algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes using R. Data science training encompasses a conceptual understanding of Statistics, Time Series, Text Mining and an introduction to Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases on Media, Healthcare, Social Media, Aviation, and HR.

Related paths/tracks: Data Analytics with R Certification Training, Advanced Predictive Modelling in R Certification Training

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Data Science: R Basics

Platform: edX

Description: The first in edX’s Professional Certificate Program in Data Science, this course will introduce you to the basics of R programming. You can better retain R when you learn it to solve a specific problem, so you’ll use a real-world dataset about crime in the United States. You will learn the R skills needed to answer essential questions about differences in crime across the different states. The demand for skilled data science practitioners is rapidly growing, and this series prepares you to tackle real-world data analysis challenges.

Related path/track: Statistics and R

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An Introduction to R for Data Science

Platform: Experfy

Description: This R course is step-by-step. In every new tutorial, students build on what they had already learned and move one extra step forward. After every video, you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course.

Related paths/tracks: Data Wrangling in R, Data Science Masterclass with R, Probability and Statistics for Data Science with R

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Data Science Course Online

Platform: Intellipaat

Description: This data scientist course lets you master skills, such as data analytics, R programming, statistical computing, machine learning algorithms, k-means clustering, and more. It includes multiple hands-on exercises and project work in the domains of banking, finance, entertainment, etc. Intellipaat’s online data science courses are well recognized across 500+ employers helping you to land your dream job.

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Learning R

Platform: LinkedIn Learning

Description: Learn the basics of R and get started finding insights from your own data, in this course with professor and data scientist Barton Poulson. The lessons explain how to get started with R, including installing R, RStudio, and code packages that extend R’s power. You also see first-hand how to use R and RStudio for beginner-level data modeling, visualization, and statistical analysis. By the end of the course, you’ll have a thorough introduction to the power and flexibility of R, and understand how to leverage this tool to explore and analyze a wide variety of data.

Related paths/tracks: R for Data Science: Lunchbreak Lessons, R Programming in Data Science: Setup and Start, R for Excel Users, Data Wrangling in R

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Programming with R

Platform: Pluralsight

Description: In this course, Programming with R, you will learn how to manipulate different objects. First, you will learn the basic syntax. Next, you will explore data types and data structures available in R. Finally, you will discover how to write your own functions by implementing control flow statements. When you are finished with this course, you will have a foundational knowledge of R programming that will help you as you move forward to data science.

Related paths/tracks: Data Science with R, Understanding Machine Learning with R

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Data Science with R Certification Course

Platform: Simplilearn

Description: The Data Science with R programming certification training covers data exploration, data visualization, predictive analytics, and descriptive analytics techniques with the R language. You will learn about R packages, how to import and export data in R, data structures in R, various statistical concepts, cluster analysis, and forecasting. This module enables several different training options.

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Programming for Data Science with R (Nanodegree)

Platform: Udacity

Description: Learn the programming fundamentals required for a career in data science. By the end of the program, you will be able to use R, SQL, Command Line, and Git. There are no prerequisites for this program, aside from basic computer skills. With real-world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

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R Programming A-Z: R For Data Science With Real Exercises!

Platform: Udemy

Description: This course is truly step-by-step. In every new tutorial, instructors build on what students had already learned and move one extra step forward. After every video, you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course.

Related paths/tracks: Data Science and Machine Learning Bootcamp with R, R Programming: Advanced Analytics In R For Data Science

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