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R courses

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.

Courses

Introduction to R

พื้นฐานระดับทักษะ
4 hours
40.7K
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

Tracks

R Programming Fundamentals

22 hours
14.9K
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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เรียกดูหลักสูตรและแทร็กของ R

Courses

Mixture Models in R

ระดับกลางระดับทักษะ
4 hours
51
Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.

Courses

Probability Puzzles in R

พื้นฐานระดับทักษะ
4 hours
50
Learn strategies for answering probability questions in R by solving a variety of probability puzzles.

Courses

Building Response Models in R

ระดับกลางระดับทักษะ
4 hours
46
Learn to build simple models of market response to increase the effectiveness of your marketing plans.

Courses

Scalable Data Processing in R

ขั้นสูงระดับทักษะ
4 hours
40
Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

Courses

Predictive Analytics using Networked Data in R

ระดับกลางระดับทักษะ
4 hours
30
Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network

Tracks

R Programming Fundamentals

22 hours
14.9K
Level-up your R programming skills! Learn how to work with common data structures, optimize code, and write your own functions.

Tracks

Associate Data Scientist in R

88 hours
5K
Learn how to use R for data science, from data manipulation to machine learning. Gain the career-building skills you need to succeed in data science!

Tracks

Data Analyst in R

36 hours
3.1K
From exploratory data analysis with dplyr to data visualization with ggplot2—gain the career-building R skills you need to succeed as a data analyst!

Tracks

Statistician in R

52 hours
956
A statistician collects and analyzes data and helps companies make sense of quantitative data, including spotting trends and making predictions.

Tracks

Statistics Fundamentals in R

20 hours
911
Discover the power of statistics in R. Learn the key statistical concepts, topics, and techniques used by data scientists and statisticians every day.

Tracks

Data Visualization in R

12 hours
699
Bring your data into focus with data visualizations in R using ggplot2. Learn the graphical and plot-building skills to tell better data stories.

Tracks

Analyzing Genomic Data in R

16 hours
577
Start exploring the world of computational biology with essential Bioconductor packages and workflows for next-generation sequencing data analysis.

Tracks

R Developer

52 hours
521
Gain the career-building skills you need to succeed as an R Developer by learning to write and package code efficiently. No coding experience needed!

Tracks

Tidyverse Fundamentals in R

20 hours
519
Import and tidy data, wrangle and visualize data, and model and communicate with data in R with the tidyverse.

Tracks

Data Scientist in R

27 hours
509
Learn data science with R, from data manipulation to machine learning, and gain the skills needed for the Data Scientist in R certification!

Tracks

Data Manipulation in R

16 hours
476
Take the pain out of data manipulation using dplyr and tidyr. Learn how to transform, sort, and filter your data, ready for quick analysis.

Tracks

Quantitative Analyst in R

67 hours
473
Ensure portfolios are risk balanced, help find new trading opportunities, and evaluate asset prices using mathematical models.

Tracks

Machine Learning Fundamentals in R

24 hours
430
Predict categorical and numeric responses via classification and regression, and discover the hidden structure of datasets with unsupervised learning.

Tracks

Time Series in R

25 hours
317
Learn how to extract meaningful insights from time series data in R. Explore how to model, forecast, and visualize time series data.

Tracks

Importing & Cleaning Data in R

14 hours
245
Gain the real-world skills you need to import and clean your data when working in R—making it possible for you to reveal the insights that matter.

Tracks

Shiny Fundamentals in R

16 hours
230
Learn how to use Shiny, a popular R package, to build highly interactive web applications and share your analyses as dashboards and visualizations.

Tracks

Statistical Inference in R

16 hours
192
A core set of skills in statistical inference necessary to understand, interpret, and tune your statistical & machine learning models.

Tracks

Marketing Analytics in R

24 hours
173
Grow the R skills you need to work with social media data, perform market basket analysis, and use machine learning to guide your marketing decisions.

Tracks

Text Mining in R

16 hours
144
Discover text mining in R and learn how to extract exciting insights from tweets, product reviews, and books through sentiment analysis in R.

Tracks

Big Data in R

16 hours
132
Work with big data in R via parallel programming, interfacing with Spark, writing scalable & efficient R code, and learn ways to visualize big data.

Tracks

Finance Fundamentals in R

28 hours
131
Gain the introductory skills you need to make data-driven financial decisions in R—using the xts, zoo, tidyquant, and PortfolioAnalytics packages.

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R Project

blogs

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 นาที

blogs

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 นาที

cheat sheets

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 นาที

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

    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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