I had to look in other materials to understand most of the algorithms, the way it was presented just reading the material doesn't help much. As a result, I ended up preferring to just read the material rather than watch it. So, I think it could be a more dynamic class to improve didactics.

This course is inappropriately calibrated. At best, it is a fair refresher for someone who has already taken a graduate level course in Bayesian statistics. The coding assignments are do-able, but the course content does not include an example solution to the ungraded coding homework assigments. The lectures are fair to poor, with notes that neither visually convey the intuition of each method nor the mathematical details. In summary, the class is an ok 8 hour refresher for someone who already knows Bayesian statistics and MCMC.

The presenter simply read the notebooks, didn't add anything. He seemed bored most of the time.

Showed an example where the predicted distributions were consistent but didn't show one where they were not consistent. There were many concepts in the course that would benefit from more demonstrations of how the algorithms work, rather than describing them.

I was disappointed with this course and will avoid courses from Databricks in the future.