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

## 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.

## 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.

## 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