Data Science in a Box contains the materials required to teach (or learn from) an introductory data science course using R, all of which are freely-available and open-source. They include course materials such as slide decks, homework assignments, guided labs, sample exams, a final project assignment, as well as materials for instructors such as pedagogical tips, information on computing infrastructure, technology stack, and course logistics.
See datasciencebox.org for everything you need to know about the project!
Note that all materials are released with Creative Commons Attribution Share Alike 4.0 International license.
You can file an issue to get help, report a bug, or make a feature request.
Before opening a new issue, be sure to search issues and pull requests to make sure the bug hasn’t been reported and/or already fixed in the development version.
By default, the search will be pre-populated with
You can edit the qualifiers (e.g.
is:closed) as needed.
For example, you’d simply remove
is:open to search all issues in the repo, open or closed.
If your issue involves R code, please make a minimal reproducible example using the reprex package. If you haven’t heard of or used reprex before, you’re in for a treat! Seriously, reprex will make all of your R-question-asking endeavors easier (which is a pretty insane ROI for the five to ten minutes it’ll take you to learn what it’s all about). For additional reprex pointers, check out the Get help! section of the tidyverse site.
Please note that the datascience-box project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.