SP
Oct 11, 2020
An amazing course! The assignments and quizzes can be insanely difficult espceially towards the conclusion.. Requires textbook reading and relistening to lectures to gather the nuances.
OD
Jan 29, 2018
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.
By Ruiliang L
•Mar 23, 2021
Excellent course. Assignments are challenging but once you figure them out you will have a solid understanding of PGM.
By Jerry R
•Jan 29, 2018
Great course! It is pretty difficult - be prepared to study. Leave plenty of time before the final exam.
By rishi c
•May 7, 2020
Plz give practical assignments in Python. Matlab is not free and not many and neither myself know Matlab.
By Una S
•Sep 6, 2020
Amazing! This is the first specialization that I have finished and it feels amazing! Daphne was amazing!
By Liu Y
•Aug 27, 2018
Great course, great assignments I indeed learn much from this course an the whole PGM ialization!
By Anil K
•Nov 9, 2017
Awesome course... builds intuitive thinking for developing intelligent algorithms...
By Ivan V
•Oct 20, 2017
Excellent course. Programming assignments are excellent and extremely instructive.
By Khalil M
•Apr 3, 2017
Very interesting course. Several methods and algorithms are well-explained.
By Stian F J
•Apr 20, 2017
Tougher course than the 2 preceding ones, but definitely worthwhile.
By 张文博
•Mar 6, 2017
Excellent course! Everyone interested in PGM should consider!
By Sriram P
•Jun 24, 2017
Had a wonderful Experience, Thank you Daphne Ma'am
By Wenjun W
•Jul 30, 2017
Very challenging and fulfilling class!
By 郭玮
•Nov 12, 2019
Great course, very helpful.
By Hippolyte W
•Oct 5, 2022
Definitively worth it !
By Yang P
•Jun 20, 2017
Very useful course.
By Alexander K
•Jun 4, 2017
Thank You for all.
By Alireza N
•Jan 12, 2017
Excellent!
By Allan J
•Mar 4, 2017
Great content. Explores the machine learning techniques with the tightest coupling of statistics with computer science. The Probabilistic Graphical Models series is one of the harder MOOCs to pass. Learners are advised to buy the book and actually read it carefully, preferably in advance of listening to the lectures. The quality of the course is generally high. The discussion is a little muddled at the very end when practical aspects of applying the EM algorithm (for learning when there is missing data) is discussed.
By James C
•Mar 3, 2021
The lecturer and theoretical aspects of the course are great. The final assessment is challenging but a couple of the questions are ambiguous and imprecise - which was a little frustrating given the quality of the content of the lectures. Honours assignments are now quite dated and contain some excruciating bugs. Overall, worthwhile to take the course, but the assignments (and especially the optional content) could do with revision.
By nicu@ionita.at
•May 21, 2017
This was a very interesting specialization and beside the theoretical information in the videos I liked very much the programming assignments, which helped very much with understanding more deep the matter. The PAs were also very challenging, especially the ones in the learning part (course 3).
By Vincent L
•Jun 5, 2018
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.
By Gorazd H R
•Jul 7, 2018
A very demanding course with some glitches in lectures and materials. The topic itself is very interesting, educational and useful.
By Luiz C
•Aug 27, 2018
Great course, though with the progress of ML/DL, content seems a touch outdated. Would
By AlexanderV
•May 13, 2021
Octave programming assignments, instead of Python
By Paul-Andre R
•Mar 19, 2021
It was a good class. I have been cruising through the 1st, 2nd and this third class of the specialization..... until the last week. The last assignment and the final exam were significantly more challenging for me that the previous ones. I had not budgeted enough time. It is fine to make the class hard..... however, I think it should have been uniformly hard..... not suddenly and unexpectedly harder at the very end, after I have invested many week-ends in this learning.