Currently, the Data Science curriculum does not include a class using R. However, R is increasingly popular in data science research and is often listed in job postings as a requirement or preference along with Python. So, for those interested in learning a little R to supplement their Python skills (or jump right into R!) these resources are here to help.
Download R
The first step is to download R, which you can do here. I would also highly recommend downloading RStudio, the integrated development environment (IDE) for R. Both R and RStudio are free.
The Library also runs semi-regular R workshops. Check the Workshops page to learn more.
We have quite a few R books available through the library. Some of these are only accessible via a physical book copy, but many are available as e-books. Try searching the library catalog UC Library Search for "R programming" to see our entire collection.
In the meantime, these books may be useful.
One of the main benefits of R is the vast array of pre-existing packages (also called libraries) written by other R users and available for installation.
All official R packages are available through CRAN (Comprehensive R Archive Network). There are a lot of R packages available; this list of recommended R packages is a good starting point.
Here are some resources for popular data science-related R packages. Also be sure to check out all of RStudio's cheatsheets.