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R is the second most sought after language in data science behind Python, so gaining mastery of R is a prerequisite to a thriving career in the field. Whether you’re an experienced developer or a newbie considering a career move, here are some excellent resources so you can get started with R.
[Related Article: Data-Driven Exploration of the R User Community Worldwide]
What is R?
R is a programming language and environment designed for statistical analysis. It’s used mainly by data miners and statisticians. It’s a free resource and runs on a wide variety of platforms, including UNIX, Windows, and Mac OS.
It has thousands of well-documented extensions and is cross-platform compatible. It’s not quite as popular outside of the field of data science, but it’s one of the best options for exploring datasets in a deep dive manner or for going after data insights for a single time.
Head over to the R sight and download a copy of R, so you’re ready to get started.
Free R Resources for Beginners
Let’s take a look at how a beginner might break into R. It’s not quite as friendly as Python, but it’s definitely accessible with good resources and practice.
Platforms and Documentation
r-bloggers.com: R-bloggers is a collection of blogs designed by R experts that covers a wide range of R topics. No matter what you’re curious about or have an issue with, R-bloggers has it covered.
R for Data Science: This classic handbook provides resources and documentation. It’s available for free on the website, or you can purchase a physical copy from Amazon.
Hands-on Programming with R: Garrett Grolemund’s classic is a practical, hands-on approach to R programming. It gives you the instruction you need plus practical programming skills to begin with R right from the very beginning.
Codecademy: Codecademy’s mission is to bring development knowledge even to beginners, and its R offers are no different. While many of the lessons will require a membership, it does offer a basic set of courses to get you started.
edX.org: EdX offers a range of free R courses to get you started, but we recommend starting with Microsoft’s Introduction to R for Data Science for a comprehensive overview. The courses cost nothing and are offered asynchronously. Some do come with official certification for a fee.
Free R Resources for Developers
If you’ve already got some development experience under your belt, these resources could be a great way to get started with R by utilizing your current experience. Even better, they’re free.
Platforms and Documentation
storybench.com: Storybench is an experiential learning platform designed to provide exercises in digital storytelling. They offer projects in R, most notably “How to Explore Correlations in R.” Once you’ve gotten the basics, the next logical step is to take on projects for hands-on learning.
R Programming for Data Science: This option is available for free (though you can choose to donate in support of the project). It offers full resources for learning R and understanding key data science principles. If you upgrade the package, the online book comes with a full video suite.
Text Mining with R: Another book available for free on the website, this option offers a targeted approach to text mining with a full Github repository as support.
R in Action: Another entirely free resource for business developers. If you’ve already got an established career in development in the business world, this could be an excellent resource for getting started with R in the business world.
Coursera: Johns Hopkins’s popular partnership with Coursera, “Data Science, Foundations Using R” is a great way for developers to build skills to break into the field of Data Science.
edX + Harvard: X Series Program in Data Analysis for Life Sciences is a course series designed to implement both learning R and real-life projects for a full learning experience. You can upgrade to an official learning certificate for a fee or take the individual courses for free.
Paid Resources for Beginners and Beyond
Sometimes, you’ve got to invest a little in your learning experience. Here are a couple of things that can really jumpstart your R-programming skills if you’ve got some wiggle room in your budget.
Getting Started with R: A primer on using R for the biological sciences. It contains valuable information for getting started on statistical analysis using the R programming language.
flowingdata.com: Flowingdata is a membership site designed to elevate your visualizations. It’s another excellent way to get experiential learning with R projects.
Rstudio: It’s not cheap, but if you’re serious about making a career in R, you’ll want to get it. Save up and invest. They do, however, have a series of free webinars you can peruse.
Bonus! More Blogs and Newsletters
https://blog.revolutionanalytics.com/r/ : Blog designed to highlight milestones in Data Science and includes a range of topics including both R and Python for you multilingual developers out there.
https://journal.r-project.org/: Open access, refereed journal detailing the latest in R-programming news and projects. Papers have a focus on accessibility, and the articles are tended to reach a wide audience.
https://morningcupofcoding.com/: Offers a wide range of curated coding articles, including R programming. Check their back issues for articles of interest.
: ODSC’s general weekly newsletter
provides members with trending topics in the fields of modeling, tools & platforms, and more.
Getting Started with R Programming
[Related Article: Where is Data Science Heading? Watching R’s Most Popular Packages May Have the Answer]
While both Python and R are invaluable resources for getting started in Data Science, the statistical capabilities of R are in wide demand. Whether you’re new to the world of coding or an experienced developer, R can open doors into the world of Data Science.