Open bpbond opened 6 years ago
Some resources to consider, perhaps for "homework" or background reading:
Git and GitHub
The (in)famous Git book. I still firmly believe that there is no better way to get a firm git foundation than properly working through (with terminal open) the first few chapters. That said, there are lots of other nice interactive ways to learn it, such as those linked here.
Introduction to R Data processing in R
If I were teaching a course on R, I would probably make a curriculum that follows, in order:
Another great resource that just occurred to me is Claus Wilke's Fundamentals of Data Visualization. It's not strictly R-related, but the approach to visualization fits naturally with the ggplot2
philosophy (and, not surprisingly, all of the plots in there are generated with ggplot2
).
Haven't looked too deeply, but RStudio's Education organization has lots of teaching resources.
Also, awesome-r is mostly a list of good packages for various applications, but towards the bottom, it links to some R learning resources as well.
I'll try to look at some of these links more closely later this week.
Another possibility: the swirl package. I tried out the first 5 minutes and looks like it has potential.
swirl
seems like a great place to start. I like that it's right in your local R(studio) session. I also really like that you can write your own lessons. There's a good chance I'll end up using it in my GWU course.
My vote would be to use Swirl to get comfortable in R, and then to move to R for Data Science.
Regarding git, I would probably recommend CodeAcademy's interactive Git tutorial paired with background reading from Pro Git. Once she wraps her head around the basics, I would also encourage her to start using git to manage her R lessons.
Just jotting down some thoughts -- we can discuss later today.