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R is a language for data analysis, statistics, and machine learning. DataCamp’s expert-led R courses offer interactive practice with projects to build job-ready skills fast. Start learning R today and unlock new data science opportunities.

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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

BasicSkill Level
4.8+
32.6K
4 hours
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

12.1K
22 hours
Level-up your R programming skills! Learn how to work with common data structures, optimize code, and write your own functions.

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Browse R courses and tracks

Course

Introduction to Bioconductor in R

IntermediateSkill Level
4.8+
552
4 hours
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

Course

Unsupervised Learning in R

IntermediateSkill Level
4.7+
545
4 hours
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Course

Machine Learning with caret in R

IntermediateSkill Level
4.8+
529
4 hours
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Course

Generalized Linear Models in R

IntermediateSkill Level
4.8+
515
4 hours
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

Course

Foundations of Inference in R

IntermediateSkill Level
4.7+
505
4 hours
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Course

Supervised Learning in R: Regression

IntermediateSkill Level
4.6+
485
4 hours
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Course

RNA-Seq with Bioconductor in R

IntermediateSkill Level
4.7+
480
4 hours
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Course

Data Manipulation with data.table in R

BasicSkill Level
4.7+
480
4 hours
Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

Course

Visualization Best Practices in R

BasicSkill Level
4.8+
469
4 hours
Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.

Course

Web Scraping in R

IntermediateSkill Level
4.7+
462
4 hours
Learn how to efficiently collect and download data from any website using R.

Course

Dealing With Missing Data in R

BasicSkill Level
4.7+
447
4 hours
Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Course

Intermediate Importing Data in R

IntermediateSkill Level
4.8+
438
3 hours
Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.

Course

Experimental Design in R

IntermediateSkill Level
4.7+
433
4 hours
In this course youll learn about basic experimental design, a crucial part of any data analysis.

Course

Communicating with Data in the Tidyverse

BasicSkill Level
4.8+
432
4 hours
Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Course

Cluster Analysis in R

IntermediateSkill Level
4.8+
430
4 hours
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Course

Intermediate R for Finance

BasicSkill Level
4.8+
349
5 hours
Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

Course

Categorical Data in the Tidyverse

BasicSkill Level
4.7+
328
4 hours
Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

Course

Inference for Numerical Data in R

AdvancedSkill Level
4.8+
307
4 hours
In this course youll learn techniques for performing statistical inference on numerical data.

Related resources on R

R Project

blog

The Top 8 R Project Ideas for 2026

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

14 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

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    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 2025?

    Absolutely, R is worth learning in 2025, 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.

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