In a recent article at opensource.com, I offer up some reasons why now is the time to learn R: data scientists are in high demand, R is the natural language for data scientists, and companies around the world are using R (and hiring R programmers) to make sense of new data sources. Sharp Sight Labs also offers some excellent reasons why you should choose the R language for data science.
So, if you'd like to take the plunge, here are some tips to help you get started with R:
- First, download R. I recommend using Revolution R Open for speed, and RStudio for an excellent interface for writing code. Both are free.
- Read a beginner's tutorial, or take an online course. We have some recommendations in our Getting Started with R guide.
- Find yourself a data project to solve with R, and try it! There's no better way to learn than doing. If you're stuck for inspiration, there are many free online data sources you can use with R — explore one of them!
- If you get stuck, search the R tag on StackOverflow for help. (If you have a budget, you can also purchase professional support for R.)
Got any other tips for beginners getting started with R? Let us know in the comments.
May I suggest my Beginner's Guide to R at Computerworld: http://cwrld.us/IntroToR
Posted by: Sharon Machlis | January 29, 2015 at 05:06
"R programming" course on Coursera is quite nice: https://www.coursera.org/course/rprog
Posted by: me | January 29, 2015 at 05:57
Coursera has a Data Science Specialization track that teaches R. It also teaches Data Science - good place to start (I am doing it now).
Posted by: Patrick Klien | January 29, 2015 at 08:14
David, I echo what the other commentors have said: I think that coursera has more or less "solved the R education problem".
After that, google searches which link to stackoverflow questions solves most problems.
Posted by: Ari | February 06, 2015 at 14:14