Bad choice of content. Focus too much on the specific case of table CPDs, missing the big picture.

Great course, though with the progress of ML/DL, content seems a touch outdated. Would

Great course, great assignments I indeed learn much from this course an the whole PGM ialization!

The course is very involved but Daphne makes its palatable. The course open a new world of new possibilities where one can apply PGMs to get concrete understanding of relationships between events and phenomena in any discipline; from social sciences to natural sciences.

Good course, but the material really needs a refresh!

A very demanding course with some glitches in lectures and materials. The topic itself is very interesting, educational and useful.

Difficult; requires textbook reading to complete. I could not get samiam to work so I skipped the initial PA. The PA are challenging as well but well worth it if you want to understand how to implement PGMs.

The course facilitates learning - and reinforces acquired knowledge through the simple principle of honest effort: students are not given all the answers... but they are 'nudged' in the right direction & guided towards fruitful questions; in a way, it's the perfect course!

Yeah! I managed to finish PGM. I feel ready to explore further. PGM 3 is really helpful. Although many details are not fully discussed, some important intuitions are well illustrated, like EM algorithm and its modification in case of incomplete data. Also, the way the teacher teach set an good example for me to learn to demonstrate complicated things in an easy and vivid way. Thank you so much!

very good course for PGM learning and concept for machine learning programming. Just some description for quiz of final exam is somehow unclear, which lead to a little bit confusing.