CDT DIS

Principles of Data Science. Quite a nice rigorous course, but rather particle-physics-heavy, making some of the jargon used a bit difficult to parse.

Applied Data Science. Whistle-stop. A bit messy at the start, but then became a good overview of a lot of different techniques.

Statistics of Data Science. Probably one of the best courses I've ever taken at Cambridge. I never really got on with Bayesian statistics, but that's all changed.

Applications of Machine Learning. Essentially consisted of taking an excellent textbook, and trying and failing to communicate it out loud. Later sections of the course were very rushed and lacked depth, as the scope of the course was a bit too ambitious.