- Course website
- 2021 Schedule
- GitHub repo (my fork)
- Bayesian Data Analysis (3e) (BDA3) (exercise solutions)
- Chapter Notes
- Video lectures or individually lists here
- Lecture slides
The following are recommendations from the course creators on how to take the course.
The recommended way to go through the material is:
- Read the reading instructions for a chapter in the chapter notes.
- Read the chapter in BDA3 and check that you find the terms listed in the reading instructions.
- Watch the corresponding video lecture to get explanations for most important parts.
- Read corresponding additional information in the chapter notes.
- Run the corresponding demos in R demos or Python demos.
- Read the exercise instructions and make the corresponding assignments. Demo codes in R demos and Python demos have a lot of useful examples for handling data and plotting figures. If you have problems, visit TA sessions or ask in course slack channel.
- If you want to learn more, make also self study exercises listed below.
My notes are published as a website here.