By Lucas | January 13, 2015
There’s no doubt that the ability to analyze data and do predictive modeling by programming in R is a very valuable skill, whether you are looking to learn it for a college statistics class or one of a great many great jobs that utilize R. If you are trying to get started on your own, you may find it is a little tricky, however. While there are tons of sites in the Codecademy model to get started with certain languages like Javascript, PHP, CSS, or HTML, there are fewer options for getting started with R. Fortunately, some of the options that are out there are truly first class. I started working with R last spring and have looked at a number of sites for learning R. My favorites follow.
CodeSchool
If all you are looking for is a beginner’s tutorial in R that won’t take more than an hour or two, the free “Try R” tutorial at CodeSchool is a great option. This is a guided tutorial. It doesn’t go too deep, but if you have a lot of experience in another language or are just looking for the basics, this might be just what you need to transition to R syntax. Look for the “Electives Path” after you register.
DataCamp
DataCamp is a terrific site in the Codecademy style. It’s a series of guided tutorials, with explanation on the left, and problems to code on the right in the console. You are given partial solutions to complete. What really appealed to me about DataCamp is that the instructors who set up the courses haven’t attempted to just teach R coding, they attempted to teach you how to use R to work with data and understand data science better.
When I started using DataCamp over the summer, all of the courses were free. The original courses are still free. Since then, they have added paid courses as well, some of which are pretty pricey (up to $799). At a minimum, the free courses are certainly worth your time.
Johns Hopkins Data Science Specialization on Coursera
As I’ve returned to coding after a 15 year break, I’ve realized that guided tutorials such as DataCamp and CodeSchool have become all the rage. I may do a separate blog post on this another time, but I believe that while those types of tutorials have value, they are best used in conjunction with open ended problem solving. That’s why I highly recommend the Johns Hopkins Data Science Specialization on Coursera.
I recently completed this challenging specialization of 10 courses and am awaiting my final certificate. Each class is one month long and focuses on a different aspect of data science, but they all use R. How deep into the sequence you need to go would obviously depend on your goals. Course 2, R Programming, is the first course that focuses exclusively on programming in R.
These courses can be taken for free or for $50 if you want to receive a “verified certificate.” If you plan on taking the entire course of 10 classes, keep in mind that enrollment in the final capstone course requires that you pass the previous 9 courses with a verified certificate.
Kaggle
More recently, I’ve turned my attention to Kaggle. While the Johns Hopkins program was excellent in many respects, one of the most significant weaknesses I’m finding is that it only skimmed the surface of machine learning with R. Kaggle is a data science competition site that gives competitors a chance to hone their machine learning skills in a language of their choice. While Python seems to be the most used language by competitors, there are R tutorials for beginners, and my early impressions are that a fair number of competitors (who you can interact with on the Kaggle forums) are using R as well. If your data science skills develop to a really high level, Kaggle does offer cash prizes to the winners of many of its competitions.
R-Bloggers
R-Bloggers is an incredible resource for tutorials, tips, and news about what is happening in the world of R. Bloggers from all over the world contribute to this site, and once you have started following it, you’ll have a hard time not checking it every day since it is constantly being refreshed with new posts.