(Or, “how to teach professionals to teach themselves R”).
Background: I taught myself R in 2014 from public web resources, and since then have steered several cohorts of data analysts at my organization through various R curricula, adapting based on their feedback.
This is geared toward people teaching themselves R outside of graduate school (I perceive graduate students to have more built-in applications and more time for learning, though I don’t speak from experience). I say “students” below but I am referring to professionals. This advice assumes little or no programming experience in other languages, e.g., people making the shift from Excel to R (I maintain that Excel is one of R’s chief competitors). If you already work in say, Stata, you may face fewer frustrations (and might consider DataCamp’s modules geared specifically to folks in your situation).
I’ve tried combinations of Coursera’s Data Science Specialization, DataCamp’s R courses, and the “R for Data Science” textbook. Here’s what I’ve learned about learning and teaching R and what I recommend.
I see three big things that will help you learn R:
- A problem you really want to solve
- A self-study resource
- A coach/community to help you