Next term, I'm going to teach an introductory Data Science class for the first time. In the past, others have taught it in either R or Python. My first inclination was to teach it in R because the language is specifically for statistics (and not a general programming language like Python). However, I see a lot of promise in Python's Pandas library. I haven't used Pandas myself, but I have more than enough time that I could familiarize myself with it.
What are your thoughts on R vs Python vs a bit of both?
Ultimately, the Data Science curriculum exposes students to both. Which do you think is more appropriate to begin?
Prereqs include CS1 (C++) and Statistics
Topics include the analytics life cycle, data integration and modeling, relational databases and SQL, text processing and sentiment analysis, and data visualization. Emphasis is placed on reproducible research, code sharing, version control, and communicating results to a non-technical audience.
First of two DS classes as part of a DS certificate (Minor is < Certificate is < Major) with predominantly Comp Sci and Stats majors enrolled
I am currently teaching the Advanced DS class (the follow-up course) with a concentration on R, but that could potentially change in the future as well. Sooner or later, if they complete the certificate, they will get experience in both R and Python. The question is which comes first.
I can choose the textbook, but will give strong preference to free, online resources