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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.

课程

R 入门

基础技能水平
4.8+
2,365 条评价
4小时
掌握 R 数据分析基础，包括向量、列表和数据框，并用真实数据集实践 R。

学习路径

R编程基础

4.4+
14 条评价
22小时
提升你的 R 编程技能！学习如何使用常见数据结构、优化代码，并编写自己的函数。

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浏览 R 课程和学习路径

课程

Network Analysis in R

中级技能水平
4.7+
120 条评价
4小时
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

课程

Inference for Categorical Data in R

高级技能水平
4.8+
107 条评价
4小时
In this course youll learn how to leverage statistical techniques for working with categorical data.

课程

Communicating with Data in the Tidyverse

基础技能水平
4.8+
190 条评价
4小时
Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

课程

Modeling with tidymodels in R

中级技能水平
4.8+
173 条评价
4小时
Learn to streamline your machine learning workflows with tidymodels.

课程

Quantitative Risk Management in R

基础技能水平
4.8+
80 条评价
5小时
Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

课程

Credit Risk Modeling in R

中级技能水平
4.7+
82 条评价
4小时
Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

课程

Sentiment Analysis in R

中级技能水平
4.7+
95 条评价
4小时
Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

课程

Hyperparameter Tuning in R

高级技能水平
4.8+
51 条评价
4小时
Learn how to tune your models hyperparameters to get the best predictive results.

课程

Categorical Data in the Tidyverse

基础技能水平
4.7+
162 条评价
4小时
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.

课程

Fraud Detection in R

中级技能水平
4.7+
36 条评价
4小时
Learn to detect fraud with analytics in R.

课程

Visualizing Geospatial Data in R

中级技能水平
4.5+
86 条评价
4小时
Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

课程

Data Manipulation with data.table in R

基础技能水平
4.6+
21 条评价
4小时
Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

课程

Market Basket Analysis in R

中级技能水平
4.8+
83 条评价
4小时
Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.

课程

Machine Learning in the Tidyverse

中级技能水平
4.8+
107 条评价
5小时
Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

课程

Bond Valuation and Analysis in R

中级技能水平
4.8+
82 条评价
4小时
Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

课程

Building Dashboards with shinydashboard

基础技能水平
4.6+
74 条评价
4小时
Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

课程

GARCH Models in R

高级技能水平
4.8+
95 条评价
4小时
Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

课程

Developing R Packages

中级技能水平
4.7+
139 条评价
4小时
Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

R 相关资源

R Project

博客

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分钟

博客

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分钟

速查表

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分钟

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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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