Learning R programming can be an adventure, especially when you have access to an abundance of free resources. Whether you’re starting or looking to sharpen your skills, the internet is teeming with tutorials, interactive platforms, and insightful blogs that won’t cost you a penny. Here are 35 incredible resources that can help you learn R for free, from the comfort of your own keyboard.
1. CRAN Manuals
CRAN (Comprehensive R Archive Network) hosts a collection of official R manuals. These manuals are a priceless resource for understanding the core of R language.
- Pros: Official documentation; detailed.
- Cons: Can be dense for beginners.
- Access: Free.
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2. R for Data Science
R for Data Science by Hadley Wickham and Garrett Grolemund is an online book that guides you through the essentials of using R for data wrangling, modeling, and visualization.
- Pros: Comprehensive guide; exercises included.
- Cons: Primarily focuses on the ‘tidyverse’ packages.
- Access: Free.
3. Swirl
Swirl teaches R programming and data science interactively within the R console itself.
- Pros: Interactive learning; covers a broad range of topics.
- Cons: A hands-on approach that might require supplemental resources.
- Access: Free.
4. DataCamp’s Introduction to R
DataCamp’s Introduction to R offers a free introductory course covering basic R concepts, vectors, and data frames.
- Pros: Interactive exercises; beginner-friendly.
- Cons: Only the introduction is free; subsequent courses require payment.
- Access: Free (for the introductory course).
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5. DataQuest
DataQuest provides an interactive curriculum that includes R. The first few missions in the ‘Data Analyst in R’ path are free.
- Pros: Interactive; well-structured.
- Cons: Full path requires a subscription.
- Access: Some free content; offers a free trial.
6. Code School’s Try R
Code School’s Try R (Pluralsight) courses are aimed at beginners and provide a solid introduction to R programming essentials.
- Pros: Gamified learning; great for beginners.
- Cons: Only a basic introduction.
- Access: Free.
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7. Quick-R
Quick-R is a website offering a comprehensive overview of R for those with previous experience in software like SAS or SPSS.
- Pros: Concise and clear; perfect for transitioning from other software.
- Cons: Not as in-depth for complete beginners to programming.
- Access: Free.
8. R-bloggers
R-bloggers is an R blog aggregator that sources articles from across the web related to R programming.
- Pros: Diverse range of topics; frequent updates.
- Cons: Quality can vary since content comes from multiple authors.
- Access: Free.
9. RWeekly
RWeekly curates highlights from the R community, including tutorials, packages, and articles.
- Pros: Weekly updates; community-sourced.
- Cons: Might be overwhelming for beginners.
- Access: Free.
10. RPubs
RPubs allows R users to publish their R Markdown documents online for free.
- Pros: Access to a wide variety of tutorials and examples.
- Cons: Content quality and complexity can vary.
- Access: Free.
11. Coursera
Coursera offers free R programming courses from universities and companies, though you’ll need to pay if you want a certificate. Two popular courses are R Programming by Johns Hopkins University and Data Science: Foundations using R Specialization.
- Pros: University-level courses; comprehensive topics.
- Cons: Certificates and graded assignments require payment.
- Access: Free to audit.
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12. edX
edX offers a selection of courses created by institutions like Harvard and MIT. As with Coursera, auditing the course is free, certificates cost extra.
- Pros: High-quality courses.
- Cons: Paid certificates.
- Access: Free to audit.
13. Tidyverse
The Tidyverse website has a learn section linking to articles, tutorials, and online books focusing on the tidyverse collection of R packages.
- Pros: Focused content; well-maintained documentation.
- Cons: Specific to tidyverse packages.
- Access: Free.
14. The R Journal
The R Journal is a peer-reviewed open-access journal that features short to medium length articles covering topics that might interest R users.
- Pros: Peer-reviewed; covers cutting-edge techniques.
- Cons: Articles can be very specialized and technical.
- Access: Free.
15. R Blogging Tutorial
R Blogging offers a comprehensive tutorial on how to learn R, including a step-by-step guide and resources to use.
- Pros: Organized learning path; aggregates multiple resources.
- Cons: Requires motivation and self-discipline to follow through.
- Access: Free.
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16. Stack Overflow
Stack Overflow’s R questions can be an excellent resource for solving specific coding issues and learning from real-world problems.
- Pros: Large, engaged community; practical answers.
- Cons: Varied quality of responses; can be intimidating for complete beginners.
- Access: Free.
17. GitHub
GitHub hosts many R-related projects. You can find a wealth of R packages along with their source code, which can provide real-world examples of R at work, such as the Tidyverse GitHub page.
- Pros: Access to real-world applications; ability to contribute to projects.
- Cons: Not structured for learning.
- Access: Free.
18. Shiny from RStudio
RStudio Shiny provides tutorials to get you started with Shiny, an R package that makes it easy to build interactive web apps straight from R.
- Pros: Hands-on learning; highly practical.
- Cons: More niche; focuses on web app development in R.
- Access: Free.
19. R-exercises
R-exercises delivers practical R exercises to help improve coding skills, offering a range of difficulty levels.
- Pros: Practical and applied; various difficulty levels.
- Cons: Requires a foundation in R to get started.
- Access: Free.
20. The R Inferno
The R Inferno by Patrick Burns is a free book that tackles less well-trodden areas of R, providing insight into R’s quirks and strengths.
- Pros: Deeply insightful; humorous.
- Cons: Best for those with some R experience.
- Access: Free PDF.
21. Google’s R Style Guide
Google’s R Style Guide is a neat resource for learning how to write clean, understandable R code, which is a valuable skill for any programmer.
- Pros: Encourages best practices; clear guidelines.
- Cons: Style guides can be subjective.
- Access: Free.
22. RStudio’s Webinars
RStudio’s Webinars offer a series of free webcasts about R and RStudio, covering topics from beginner to advanced.
- Pros: Covers a range of levels; direct from RStudio experts.
- Cons: More suitable for those who have the basics down.
- Access: Free.
23. Introduction to R for Data Science
FutureLearn’s Introduction to R for Data Science presents a free course by Purdue University focusing on key topics in data science and R.
- Pros: University course; no prior experience needed.
- Cons: Some content locked after the course ends unless you pay.
- Access: Free to join.
24. Learn R Programming @ LinkedIn Learning
LinkedIn Learning offers courses on R programming, though after the first month, a subscription fee applies.
- Pros: Professionally produced courses; a broad selection.
- Cons: Only free for the first month.
- Access: Free trial for one month.
25. RStudio Cheat Sheets
RStudio Cheat Sheets are handy references for using RStudio and various R packages in the tidyverse.
- Pros: Quick reference; great for daily use.
- Cons: Supplementary material rather than learning resources.
- Access: Free.
26. R Bootcamp
Johns Hopkins R Bootcamp is an online resource by Johns Hopkins Bloomberg School of Public Health, covering the basics of R for data science.
- Pros: Specially tailored for data science applications.
- Cons: May require supplemental material for depth.
- Access: Free.
27. Bookdown
Bookdown is a platform that hosts books written in R Markdown. You can find free books on R and data science topics which you can read online.
- Pros: Free online books; wide range of topics.
- Cons: Can vary in quality as content is user-submitted.
- Access: Free.
28. VIM-R-plugin
The VIM-R-plugin is for those who wish to use Vim as their R editor. While not a learning platform, it’s a useful tool for R coding.
- Pros: Integrates with a powerful text editor; great for Vim enthusiasts.
- Cons: Learning curve for Vim itself alongside R.
- Access: Free.
29. Rice University Introduction to R Programming
Rice University’s Intro to R Programming on edx is a self-paced course covering foundational R skills.
- Pros: Designed for beginners; allows peer interaction.
- Cons: Approx. 5 weeks to completion; paid certificate.
- Access: Free to audit.
30. RDocumentation
RDocumentation aggregates documentation for all R packages available from CRAN, GitHub and Bioconductor, making it a comprehensive resource for R users.
- Pros: Extensive; search-friendly.
- Cons: Can be overwhelming due to volume of information.
- Access: Free.
31. R Graphics with ggplot2
A free online draft of the book R Graphics with ggplot2 by Kieran Healy is available, focusing on data visualization with ggplot2, one of R’s most famous packages.
- Pros: Focus on visualization; detailed examples.
- Cons: Draft form; mainly about ggplot2.
- Access: Free.
32. YouTube – R Tutorials
YouTube hosts many R tutorial channels, one such being MarinStatsLectures-R Programming & Statistics which covers an extensive range of statistical techniques using R.
- Pros: Free videos; topics range from basics to advanced statistics.
- Cons: Video quality and teaching style vary.
- Access: Free.
33. RStudio Education
RStudio Education compiles resources that include online learning, webinars, and suggested reading to learn R programming.
- Pros: Carefully curated by RStudio; encompasses various learning styles.
- Cons: More a compilation of resources than direct content.
- Access: Free.
34. ModernDive – An Introduction to Statistical and Data Sciences via R
ModernDive is an online textbook providing a solid introduction to statistical and data science methods using R.
- Pros: Engaging textbook; well-structured content.
- Cons: Emphasis on statistics might not appeal to all R learners.
- Access: Free.
35. Exercism’s R Track
Exercism.io offers a series of R exercises that range from easy to difficult, with mentoring support provided by the community.
- Pros: Mentored learning; incremental difficulty.
- Cons: Requires commitment to benefit from mentorship.
- Access: Free.
R is a powerful programming language widely used in data science, statistical analysis, and visualization. These 35 resources offer opportunities for learners at all levels to deepen their understanding of R, entirely for free or with the option of additional paid content. A combination of hands-on exercises, in-depth courses, and community support make this list comprehensive – ensuring that anyone with the drive to learn can become proficient in R programming. Whether you’re a novice just starting out or an experienced statistician looking to pivot into R, there’s something on this list that can help you reach your goals. Happy coding!
