Prof. Koller did a great job communicating difficult material in an accessible manner. Thanks to her for starting Coursera and offering this advanced course so that we can all learn...Kudos!!
The course was deep, and well-taught. This is not a spoon-feeding course like some others. The only downside were some "mechanical" problems (e.g. code submission didn't work for me).
por Boxiao M•
The lecture was a bit too compact and unsystematic. However, if you also do a lot of reading of the textbook, you can learn a lot. Besides, the Quiz and Programming task are of high qualities.
por Shawn C•
The course is great with plenty of knowledge. A little defect is about description about assignment. As the forum discussed, several quizzes may confusing.
por Shane C•
concepts in the videos are well presented. additional readings from the textbook are helpful to cement concepts not explained as thoroughly in the videos
por Hilmi E•
I really enjoyed attending this course. It is foundational material for anyone who wants to use graphical models for inference and decision making..
por Nimo F B•
Great content and easy to pick up. Only issue was with downloaded Octave software. Does not work, despite multiple downloads on different machines
por Roman S•
A good introduction to PGM, from very basic concepts to some move in-depth features. A big disadvantage is Matlab/Octave programming assignments.
por Serge S•
Thanks to this course, Probabilistic Graphical Models are not anymore an esoteric subject! I am really looking for the second part of the course.
por Jack A•
The class was very exciting and challenging, but I felt the programming assignments weren't dependent on understanding the classwork at all.
por Francois L•
Really interesting contents but it would be great to have the exercises in a more up to date programming environment (python for instance)
por Gorazd H R•
A very demanding course with some glitches in lectures and materials. The topic itself is very interesting, educational and useful.
por Ashwin P•
Great material. Course mentors are nowhere to be found and some of the problems are hard, so I'd have liked to see some guidance.
por Forest R•
Excellent introduction into probabilistic graph models. Introduced me to Baysian analysis and is quite helpful for my work.
por Иван М•
Great course, would be nicer if exercises were in Python or R and if software from first honours task worked on Mac.
por Xiaojie Z•
Some interesting knowledges about PCM, but I think I need more detailed information in the succeeding courses.
por Luiz C•
Good course, quite complex, wish some better quality slides, and more quizzes to help understand the theory
por Saurabh N•
The coding assignments can be compulsory too.
Maybe not as vast, but maybe interleaved with the quizzes
por Werner N•
Very good course. It should contain more practical examples to make the material better to understand.
por Haitham S•
Great course, however, the honors track assignments are a bit too tedious and take lots of time.
por Kevin W•
The course is pretty good. I love the way that the professor led us into the graphical models.
por Péter D•
great job, although the last PA is a huge pain / difficulty spike - more hints would be nice
por Andres P N•
There are many error in the implementations for octave. Aside from that, the course is fine
por Ahmad E•
Covers some material a little too quickly, but overall a good and entertaining course.
por Soteris S•
A bit more challenging than I thought but very useful, and very well structured
Great and well paced content.
Quizzes really helps nailing the tricky points.
por Caio A M M•
Instructor is engaging in her delivery. Topic is interesting but difficult.