Learning R: Where to Start?

When you search “R introductory courses” on Google, there are 6 million results! (as of Jan 2017) When I began seeking out where to start, there were many suggestions offered to me, but more often than not people didn’t really talk about why I should start with a particular course, what to expect, how it was presented, the things they like (or didn’t like) about them. It gets to be overwhelming with so many options available to you.

When I was trying to learn R about 2 years ago, I knew so much about what’s available to get me started, yet I felt clueless about how to get started! Obviously I didn’t read through all 6 million search results to determine which course I should focus on, but I did spent a lot of time researching about what platform offers good courses as an introductory way to learn R. I decided to take three of them: Simplilearn, Code School and Coursera. I’ll discuss each one individually, the things that I took away from each one, their pros and cons, and hopefully you won’t feel as overwhelmed as I was back then.


CodeSchool allows you to complete interactive tutorials in R and other languages. It came recommended to me by several people working in the data science world as a basic starting course. Everything is handled in browser, so you won’t need to install an IDE. Just load your favorite browser and begin learning!

Course I Took:

You probably heard about CodeSchool’s  “Try R”, so many people have recommended it as a starting place to learn R. You code in small R modules in the browser as you are learning through their course. I liked that these were more hands-on and you were actually typing the R code to get results. Each chapter has a few places where you are prompted to type in a response. It’s not a very long course, but it works well and it doesn’t cost anything. CodeSchool doesn’t have a mobile app, so you’ll need to work on your computer to complete the course. When I was done with the course, I felt more comfortable using R as I had some hands on practice under my belt. The course was not very difficult or time consuming and fit my learning style very well. I would rate the difficulty of this course at a 1 on a scale of 10.


Coursera is one of the largest online course sites available today. Many academic institutes leverage Coursera to present additional materials/courses. Each course has different amounts of deliverables, quizzes, or videos, but most courses allow you to see the syllabus and will give a rough estimation of the weekly amount of time commitment. There is also a mobile app that you can use. I liked that you can download the video lectures ahead of time and then watch them while you are on a flight or just offline.

Courses I Took:

One particular institute using Coursera is John’s Hopkins University.  Their program is the “Data Science” Specialization. It’s a series of 10 courses that you can complete and earn a certificate from the program. If you read through the page of the program description, most can complete the program within 3-6 months, but if you’re just starting to learn about data science and R, don’t worry if it takes you longer. Go at your own pace and what you feel comfortable with. There’s a new course starting every week (except for the capstone project at the end). I’ve taken a number of Coursera courses that helped with my career in data science. I’ll cover those in-depth in an upcoming post. 


Simplilearn teaches a variety of subjects using video lectures and quizzes (much like Coursera). When and if you decide to use Simplilearn, look for some online codes/coupons to reduce the cost of courses. At the time, I found a 40% coupon. After a little research, on average the coupons are 20-30% off and higher (50%) around the holidays. I know this was not a popular choice, but I started using this site because my company offered to pay for the course. Since they market themselves as learn with certificate, a lot of companies would offer to reimburse the tuition without tax. Check to see if your employer has any relationship with them!

Course I Took:

On the Simplilearn platform, I took a course titled “Business Analytics Foundation: R Tools Training”. The course was priced at $400 and provided access to the material for 6 months. The course was done with videos and quizzes and covered general statistical principles. The course’s videos felt very robotic in nature as they were read by a Microsoft Sam voice. The quizzes were very straightforward and directly from the lecture videos. I believe they could have been more interactive, potentially requiring computation in R. There were no tests or projects given during the course. It was a few hours (6-10) of listening and taking notes. The course was a simple introduction to R and its capabilities, but it felt lacking in some key areas like actual use of the R language. Simplilearn does have an app that you can use. At the time that I took the course though, there was no such app. I’ve come to learn that Simplilearn has greatly changed their course since I’ve taken it. Perhaps the new course will be a better learning experience and more hands on in it’s approach to learning. Overall difficulty would be a 2 or 3 on a scale of 10. If you’re familiar with statistical terminology, this score could be even lower.


If I were to go back and start again…

I would start with the CodeSchool “TryR” course. It definitely helped provide a solid foundation for getting started using R as a language for data analysis. After that I would move to Coursera courses and their materials for learning. There’s a number of free courses there that will help expand on the knowledge you’ve learned from CodeSchool. You could even get a degree from a school that has their courses on the site.

I can’t recommend my Simplilearn experience, as I mentioned, it was not very engaging. Based on what I’ve read about their new course offering, I would reconsider them especially if your employer is willing to pay for the program.

Also, I want to mention that Kaggle has a number of free data sets available that can be used to practice some analysis. I gained tremendous hands-on experience with these resources. I’ll guide you through a few data sets in later posts.

I’d love to hear your thoughts on some of the courses you’ve taken or would recommend. Leave a comment below and we can talk about the course. 

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See you next time, #StatHeads!

From #JoetheDataGuy

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