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R is a powerful programming language widely used for data analysis, statistics, and machine learning. DataCamp’s R courses provide interactive, expert-led training to help you master data manipulation, visualization, and modeling. With hands-on exercises and real-world projects, you’ll build practical skills from day one. Start learning R today and unlock new opportunities in data science.

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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

BeginnerSkill Level
4 hours
41.2K
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
10.7K
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

153 Projects

Course

Introduction to R

BeginnerSkill Level
4 hours
41.2K
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
8.1K
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
7.8K
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
5.8K
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
5.3K
Build Tidyverse skills by learning how to transform and manipulate data with dplyr.

Course

Introduction to Regression in R

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

Course

Introduction to Importing Data in R

BeginnerSkill Level
3 hours
3.2K
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

Course

Exploratory Data Analysis in R

IntermediateSkill Level
4 hours
2.8K
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Course

Joining Data with dplyr

BeginnerSkill Level
4 hours
2.7K
Learn to combine data across multiple tables to answer more complex questions with dplyr.

Course

Intermediate Regression in R

IntermediateSkill Level
4 hours
2.1K
Learn to perform linear and logistic regression with multiple explanatory variables.

Course

Cleaning Data in R

IntermediateSkill Level
4 hours
2K
Learn to clean data as quickly and accurately as possible to help you move from raw data to awesome insights.

Course

Hypothesis Testing in R

IntermediateSkill Level
4 hours
1.9K
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

Course

Reporting with R Markdown

IntermediateSkill Level
4 hours
1.5K
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

Course

Sampling in R

IntermediateSkill Level
4 hours
1.3K
Master sampling to get more accurate statistics with less data.

Course

Reshaping Data with tidyr

IntermediateSkill Level
4 hours
1.3K
Transform almost any dataset into a tidy format to make analysis easier.

Course

Manipulating Time Series Data in R

IntermediateSkill Level
4 hours
1.1K
Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

Course

Introduction to R for Finance

BeginnerSkill Level
4 hours
1.1K
Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Course

Time Series Analysis in R

IntermediateSkill Level
4 hours
986
Learn the core techniques necessary to extract meaningful insights from time series data.

Course

Unsupervised Learning in R

IntermediateSkill Level
4 hours
957
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Course

Writing Efficient R Code

IntermediateSkill Level
4 hours
956
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Course

Building Web Applications with Shiny in R

IntermediateSkill Level
4 hours
852
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

Course

Modeling with Data in the Tidyverse

IntermediateSkill Level
4 hours
821
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

Course

Supervised Learning in R: Regression

IntermediateSkill Level
4 hours
816
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Course

Forecasting in R

IntermediateSkill Level
5 hours
770
Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

Course

ARIMA Models in R

IntermediateSkill Level
4 hours
752
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Related resources on R

R Project

blog

The Top 8 R Project Ideas for 2025

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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