Skip to main content
HomeR

R courses

R is a highly versatile and powerful programming language, celebrated for its capabilities in statistical analysis, data visualization, and its comprehensive collection of packages.
R courses icon

Recomended For Starters

Become an R programmer and develop your R skills with interactive courses, tracks and projects, curated by real-world experts.

course

Introduction to R

BeginnerSkill Level
4 hours
19.9K
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

track

R Programming Fundamentals

22 hours
354
Level-up your R programming skills! Learn how to work with common data structures, optimize code, and write your own functions.

Not sure where to start?

Take an Assessment
154 results

course

Introduction to R

BeginnerSkill Level
4 hours
19.9K
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

course

Intermediate R

BeginnerSkill Level
6 hours
5.5K
Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

course

Introduction to the Tidyverse

BeginnerSkill Level
4 hours
7.1K
Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.

course

Introduction to Statistics in R

IntermediateSkill Level
4 hours
2.9K
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

course

Data Manipulation with dplyr

BeginnerSkill Level
4 hours
4K
Build Tidyverse skills by learning how to transform and manipulate data with dplyr.

course

Introduction to Importing Data in R

BeginnerSkill Level
3 hours
1.9K
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

course

Introduction to Regression in R

IntermediateSkill Level
4 hours
1.3K
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

course

Exploratory Data Analysis in R

IntermediateSkill Level
4 hours
1.7K
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
See More

Related resources on R

R Project

blog

The Top 8 R Project Ideas for 2024

Discover what R is and all the benefits for using it while giving examples and new ideas for a project.
Elena Kosourova's photo

Elena Kosourova

16 min

blog

Python vs R for Data Science: Which Should You Learn?

This guide will help you answer one of the most frequently asked questions of newcomers in data science and help you choose between R and Python.
Javier Canales Luna's photo

Javier Canales Luna

10 min

cheat sheet

Getting Started with R Cheat Sheet

This cheat sheet will cover an overview of getting started with R. Use it as a handy, high-level reference for a quick start with R. For more detailed R Cheat Sheets, follow the highlighted cheat sheets below.
Richie Cotton's photo

Richie Cotton

9 min


Ready to apply your skills?

Projects allow you to apply your knowledge to a wide range of datasets
to solve real-world problems in your browser

project

NYC Airbnb Data Analysis

0.75 hours
5.3K
Apply data importing and cleaning skills to extract insights about the New York City Airbnb market.

project

Exploring Airbnb Market Trends

1 hour
2.4K
Apply your importing and cleaning data and data manipulation skills to explore New York City Airbnb data.
See More

Frequently asked questions

What is R?

R is a statistical computing and graphics system, consisting of the R language and a run-time environment. Originally designed for statistical purposes, it excels in data analysis, mining, modeling, and creating visualizations. Primarily used for statistics and data science, its applications extend to AI, machine learning, financial analysis, and more. Being open-source and equipped with a wide array of functions and packages, R is popular across multiple fields including academia, finance, and social media.

Do I need any prior programming experience to start learning R?

No prior programming experience is required to start learning R. Our courses are designed to be accessible to beginners, with step-by-step guidance that makes learning R straightforward—even for those new to programming.

How can learning R benefit my career?

Learning R can significantly enhance your career, especially if you are interested in fields like data analysis, statistics, or research. As a language specifically designed for statistical analysis and data visualization, R skills are highly sought after in industries ranging from healthcare and finance to academia and marketing, opening up a wide range of job opportunities and pathways for professional growth.

How do I get started with R?

Beginning your journey with R first involves grasping its fundamental concepts—such as understanding vectors, factors, lists, and data frames. Our Introduction to R programming course covers these basics, providing a solid foundation for further exploration into the R programming language.

What is the difference between R and Python?

Python is a general-purpose programming language, developed to handle a wide range of tasks from data science to web development, making it highly versatile and popular for various applications. R, on the other hand, was created for statistical analysis and excels in data visualization and exploratory data analysis.

Is R worth learning in 2024?

Absolutely, R is worth learning in 2024, especially for those focused on specialized areas like statistical analysis, data visualization, and academic research. Despite the rapid growth of Python, R maintains a strong presence in data science and analytics, valued for its advanced statistical capabilities and dedicated community.

Does Datacamp offer an R Certification?

DataCamp offers two R certifications: Data Analyst and Data Scientist. Both are available in R or Python. If you are interested in either, check out our Certifications here.

Other technologies and topics

technologies