This an automatically generated DataCamp course. Use it as a reference to create your own interactive course.
Changes you make to this GitHub repository are automatically reflected in the linked DataCamp course. This means that you can enjoy all the advantages of version control, collaboration, issue handling ... of GitHub.
- Edit the markdown and yml files in this repository. You can use GitHub's online editor or use git locally and push your changes.
- Check out your build attempts on the Teach Dashboard.
- Check out your automatically updated course on DataCamp
A DataCamp course consists of two types of files:
course.yml, a YAML-formatted file that's prepopulated with some general course information.chapterX.md, a markdown file with:- a YAML header containing chapter information.
- markdown chunks representing DataCamp Exercises.
To learn more about the structure of a DataCamp course, check out the documentation.
Every DataCamp exercise consists of different parts, read up about them here. A very important part about DataCamp exercises is to provide automated personalized feedback to students. In R, these so-called Submission Correctness Tests (SCTs) are written with the testwhat package. SCTs for Python exercises are coded up with pythonwhat. Check out the GitHub repositories' wiki pages for more information and examples.
- Check out the DataCamp Teach documentation.
- Check out DataCamp's blog posts:
Happy teaching!