You discover early on that you need to learn R if you’re going to explore the realm of data science.
So how to learn? I started by downloading R and R Studio and installing them on my Windows laptop. I acquired a couple of books on R from Amazon – but found that I needed some more basic, hands-on introduction to R before I could really absorb what those books covered.
As I started taking the Coursera R Programming course, they recommended that I should simultaneously work through the R lessons offered in swirl – “a software package for the R programming language that turns the R console into an interactive learning environment.”
You basically learn R through R using R.
I installed it, loaded the library and with a simple
I was on my way. And I fell in love with this way of learning R.
It’s not the only way, for sure. I always love to learn from books and I will be back to my Amazon purchases shortly. The Coursera lectures are good and provide excellent theoretical background on how R works (I just finished the brain-stretching lectures on Scoping Rules).
But for just starting out with R, nothing beats the simplistic, no-frills, text-only, hands-on methodology of swirl.
swirl offers a number of different courses but I’m as green as green can be, so I’m working through “R Programming”.
The lessons are short (10 – 20 minutes each) and very logical in their progression of concepts. I come from an education background (a former Physics teacher) and I was as passionate about the pedagogy as I was about the science. Whoever authored “R Programming” remembers what it was like to start from the beginning. Everything is based on founding principles and builds upon concepts without belaboring points (as Khan Academy is apt to do on occasion).
Without moving videos, fancy graphics, voice-overs and more importantly, the emphasis of hands-on practice as you learn, swirl is a very distraction-free environment to learn R.
You know what it reminds me of? (You have to be a child of the 80’s to appreciate this.)