Take your R data science skills to the next level with the tidyverse, a package of R packages that help you do more with data.
R Courses
Learn how to program in R and use the language for a variety of roles in the data industry. R programming is an in-demand skill for data analysts and scientists, making it an excellent career investment.
Choose from a wide variety of courses at DataCamp — from our comprehensive introductions through to courses with a focus on machine learning applications and logistic regression.
- Learn at your pace
- Practice coding straight away
- Choose from 150 R courses
LOVED BY LEARNERS AT THOUSANDS OF COMPANIES
R Courses for Beginners
Introduction to R
Gain the coding skills you need to master data analysis by manipulate common data structures like vectors, matrices, and data frames in R.
Jonathan Cornelissen
Co-founder of DataCamp
Introduction to the Tidyverse
David Robinson
Principal Data Scientist at Heap
Introduction to Statistics in R
Leverage the power of statistics in R and learn how to apply these techniques to data.
Maggie Matsui
Curriculum Manager at DataCamp
Cleaning Data in R
Learn how to get from raw data to valuable insights quickly with this course on cleaning data.
Maggie Matsui
Curriculum Manager at DataCamp
Introduction to Regression in R
Get familiar with some of the most commonly used statistical models as you learn how to implement, analyze, and interpret regression analysis in R.
Richie Cotton
Curriculum Architect at DataCamp
Introduction to Writing Functions in R
Enhance your R skills using real-world data to learn how to write efficient and reusable functions.
Richie Cotton
Curriculum Architect at DataCamp
Time Series Analysis in R
Time series data can be tricky, learn the key techniques you need to pull insights from this data.
David S. Matteson
Associate Professor at Cornell University
Cluster Analysis in R
Tap into the power of cluster analysis in this course designed to develop and strengthen your intuition when using hierarchical and k-means clustering.
Dmitriy Gorenshteyn
Data Scientist @ Memorial Sloan Kettering Cancer Center
Introduction to Data Visualization with ggplot2
Dig into data visualization using ggplot2. In this course, you'll learn about plot essentials and how to create complex exploratory plots of your own.
Rick Scavetta
Rick Scavetta is a co-founder of Scavetta Academy.
Supervised Learning in R: Classification
Learn the essentials of machine learning for classification.
Brett Lantz
Data Scientist at the University of Michi
Supervised Learning in R: Regression
Discover how linear regression, generalized additive models, random forests, and xgboost can help you predict future events.
John Mount
Co-founder, Principal Consultant at Win-Vector, LLC
Multiple and Logistic Regression in R
Discover logistic regression for classification and learn how to add numerous variables to linear models.
Ben Baumer
Assistant Professor at Smith College
Case Study: Exploratory Data Analysis in R
Dive into the historical voting of the United Nations General Assembly using data manipulation and visualization skills.
David Robinson
Principal Data Scientist at Heap
R Courses for Data Scientists
Intermediate R
Move beyond the basics with R in this intermediate course that covers conditional statements, loops, and vector functions.
Filip Schouwenaars
Data Science Instructor at DataCamp
Cleaning Data in R
Learn how to get from raw data to valuable insights quickly with this course on cleaning data.
Maggie Matsui
Curriculum Manager at DataCamp
Introduction to Text Analysis in R
Tap into the importance of text with this introductory course to analyzing text data in R using the tidy framework.
Marc Dotson
Assistant Professor of Marketing, BYU Marriott School of Business
Correlation and Regression in R
Explore the relationship between two numerical quantities and learn how to best characterize those relationships graphically.
Ben Baumer
Assistant Professor at Smith College
Cluster Analysis in R
Tap into the power of cluster analysis in this course designed to develop and strengthen your intuition when using hierarchical and k-means clustering.
Dmitriy Gorenshteyn
Lead Data Scientist at Memorial Sloan Kettering Cancer Center
Multiple and Logistic Regression in R
Discover logistic regression for classification and learn how to add numerous variables to linear models.
Ben Baumer
Assistant Professor at Smith College
Time Series Analysis in R
Time series data can be tricky, learn the key techniques you need to pull insights from this data.
David S. Matteson
Associate Professor at Cornell University
Manipulating Time Series Data with xts and zoo in R
Learn how to manage and manipulate ordered observations quickly and without errors using R's xts and zoo packages.
DataCamp Content Creator
Course Instructor
Intermediate Regression in R
Improve on your existing regression in R skills by learning about linear and logistic regression.
Richie Cotton
Curriculum Architect at DataCamp
Intermediate Data Visualization with ggplot2
Create meaningful explanatory plots with ggplot2 and explore importance of data visualization with this intermediate course.
Rick Scavetta
Rick Scavetta is a co-founder of Scavetta Academy.
Supervised Learning in R: Classification
Learn the essentials of machine learning for classification.
Brett Lantz
Data Scientist at the University of Michigan
Supervised Learning in R: Regression
Discover how linear regression, generalized additive models, random forests, and xgboost can help you predict future events.
Nina Zumel
Co-founder, Principal Consultant at Win-Vector, LLC
Unsupervised Learning in R
Get into the basics of clustering and dimensionality reduction in R, so you can go from data to accurate insights more quickly.
Hank Roark
Senior Data Scientist, Boeing
Machine Learning with caret in R
Discover how to build and evaluate predictive models and gain an overview of key concepts in machine learning.
Max Kuhn
Software Engineer at RStudio and creator of caret
Hypothesis Testing in R
Explore common hypothesis tests including t-tests, proportion tests, and chi-square tests while learning when and how they should be used.
Richie Cotton
Curriculum Architect at DataCamp
Forecasting in R
Start focusing on the future with this course on time series forecasting in R.
Rob J. Hyndman
Professor of Statistics at Monash University
R Courses for Data Analysts
Introduction to Data Visualization with ggplot2
Dig into data visualization using ggplot2. In this course, you'll learn about plot essentials and how to create complex exploratory plots of your own.
Rick Scavetta
Rick Scavetta is a co-founder of Scavetta Academy.
Introduction to the Tidyverse
Take your R data science skills to the next level with the tidyverse, a package of R packages that help you do more with data.
David Robinson
Principal Data Scientist at Heap
Sampling in R
Master the fundamentals of sampling in R and get more insights from less data.
Richie Cotton
Curriculum Architect at DataCamp
Joining Data with dplyr
Dive into complex questions and sophisticated analyses by learning how to combine data from multiple datasets using dplyr.
DataCamp Content Creator
Course Instructor
Cleaning Data in R
Learn how to get from raw data to valuable insights quickly with this course on cleaning data.
Maggie Matsui
Curriculum Manager at DataCamp
Categorical Data in the Tidyverse
Get familiar with non-numerical data in this categorizing-focused course where you'll explore the tidyverse landscape.
Emily Robinson
Data Scientist at DataCamp
Data Manipulation with data.table in R
Get into the fundamentals of data manipulation using data.table, including filtering and how to select and calculate groupwise statistics.
Matt Dowle
Author of data.table
Exploratory Data Analysis in R
Get started with the graphical and numerical techniques you need to reveal data structures.
Andrew Bray
Assistant Professor of Statistics at Reed College
Reporting with R Markdown
Learn how R Markdown, a user-friendly formatting language, can help you create impactful reports.
Amy Peterson
Head of Core Curriculum at DataCamp
Data Visualization in R
Jump into data visualization with this comprehensive introductory course that focuses on using base graphics in R.
Ronald Pearson
PhD in Electrical Engineering and Computer Science from M.I.T.
Intermediate Data Visualization with ggplot2
Create meaningful explanatory plots with ggplot2 and explore the importance of data visualization with this intermediate course.
Rick Scavetta
Rick Scavetta is a co-founder of Scavetta Academy.
Visualizing Geospatial Data in R
Learn how to read, explore, and manipulate spatial data before using R to build useful maps.
Charlotte Wickham
Assistant Professor at Oregon State University
Building Web Applications with Shiny in R
Learn the skills you need to easily build interactive web apps directly in R using Shiny to bring your data to life.
kaelen medeiros
Data Scientist
Case Study: Exploratory Data Analysis in R
Dive into the historical voting of the United Nations General Assembly using data manipulation and visualization skills.
David Robinson
Principal Data Scientist at Heap
R Courses for Data Engineers
Web Scraping in R
Learn how to use R to gather and extract data from websites.
Timo Grossenbacher
Project Lead Automated Journalism at Tamedia
Exploratory Data Analysis in R
Get started with the graphical and numerical techniques you need to reveal data structures.
Andrew Bray
Assistant Professor of Statistics at Reed College
Data Manipulation with dplyr
Dive into data manipulation with dplyr, where you'll learn how to transform and manipulate data.
DataCamp Content Creator
Course Instructor
Cleaning Data in R
Learn how to get from raw data to valuable insights quickly with this course on cleaning data.
Maggie Matsui
Curriculum Manager at DataCamp
Intermediate Importing Data in R
Learn how to parse the data you need. This course explores flat files, statistical software, databases, and web-based data.
Filip Schouwenaars
Data Science Instructor at DataCamp
Writing Efficient R Code
Discover how to develop quicker R code, benchmarking and profiling, and parallel programming secrets.
Colin Gillespie
Assoc Prof at Newcastle University, Consultant at Jumping Rivers
Joining Data with data.table in R
Learn data.table, a handy tool for combining and merging datasets.
Scott Ritchie
Postdoctoral Researcher in Systems Genomics
Sampling in R
Dive into complex questions and sophisticated analyses by learning how to combine data from multiple datasets using dplyr.
Categorical Data in the Tidyverse
Ready, Set, Categorize! ! Using the Tidyverse landscape, in this course you will work with non-numerical data such as job titles and survey responses.
Emily Robinson
Data Scientist at DataCamp
Working with Dates and Times in R
Get into the fundamentals of data manipulation using data.table, including filtering and how to select and calculate groupwise statistics.
Charlotte Wickham
Assistant Professor at Oregon State University
Data Manipulation with data.table in R
Gain a deep understanding of data manipulation concepts such as filtering, selecting and calculating groupwise statistics using data.table.
Matt Dowle
Author of data.table
Reshaping Data with tidyr
To make analysis easier, convert practically any dataset into a tidy format.
Jeroen Boeye
Machine Learning Engineer @ Faktion
Reshaping Data with tidyr
To make analysis easier, convert practically any dataset into a tidy format.
Jeroen Boeye
Machine Learning Engineer @ Faktion
Working with Data in the Tidyverse
Learn how to work with data with tidyverse tools and acquire the critical skills of data taming and cleaning.
Alison Hill
Professor and Data Scientist
Manipulating Time Series Data with xts and zoo in R
Learn how to manage and manipulate ordered observations quickly and without errors using R's xts and zoo packages.
DataCamp Content Creator
Course Instructor
Intermediate Data Visualization with ggplot2
Create meaningful explanatory plots with ggplot2 and explore importance of data visualization with this intermediate course.
Rick Scavetta
Rick Scavetta is a co-founder of Scavetta Academy.