Jul 13, 2017
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!!
Oct 23, 2017
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).
par roi s•
Oct 29, 2017
I really like how Dafna is teaching the course, very clear!
It will be nice if their could be a following course that will show new frameworks and code that implements PGMs. Like the courses of deep learning where Andrew Ng is focusing mostly on the practical side.
par Anurag P•
Jan 08, 2018
The course is quite hard, however it becomes easier if you follow the book along with course. Also, programming assignments need to improved, the bugs and known issues mentioned in forum should be incorporated to prevent people from wasting time on setup issues.
par Yuxuan X•
Aug 08, 2017
Awsome course for Information/Knowledge Engineering. Although not necessary to finish all the honor assignments, it is highly recommended to implement them. Not only for comprehension, but also practice. You can actually apply them on your career or research.
par Minh N•
Mar 01, 2017
Quite a steep learning curve. Definitely not for those without prior experience in machine learning, or statistics in general. Also, I would much appreciate it if more test cases were provided in the programming assignments to help with debugging.
par Christophe K•
Oct 22, 2016
Very challenging course, but hey, if you are here, you are looking for that!
Lots of knowledge to absorb, but that leads you to a deep understanding on Probability Graphs properties.
I've learnt a lot and I really enjoyed taking this course.
par Maxim V•
Apr 29, 2020
Basic but absolutely necessary knowledge (representation). Quizzes were surprisingly easy. The best (and in my opinion absolutely necessary) part are the honor assignments, they make the course not just a little but many times better.
par José A R•
Sep 14, 2018
Excellent course. Very well explained with precise detail and practical material to consolidate knowledge.
This was my first approach to PGM and end it fascinated. Will look to learn more from this subject.
Thank you very much Daphne!!
par Chatard J•
Nov 25, 2016
Une méthode pédagogique sans faille. Des contrôles et des exercices qui permettent d'approfondir ce qu'on apprend et de faire le point en permanence. Un merveilleux voyage dans le monde des Modèles Graphiques Probabilistes.
par Justin C•
Oct 23, 2016
This was a fantastic introduction to PGM for a non-expert. It is well paced for an online course and the assignments provide enough depth to hone your knowledge and skills within the 5 week timeframe. Highly recommended.
par KE Z•
Nov 23, 2017
All Programming Assignments are challenging (Bayesian net, Markov net/CRF, and decision making), but very essential to help understand how PGM works. I definitely will enroll the second course in this specialization.
par Alexey K•
Nov 17, 2017
Thank you! It's simply incredible exercise for brain! :-) The best ever course here, which teaches one to really think and model, rather than merely click to choose most plausible answer ( like other courses do )
par Ofelia P R P•
Dec 11, 2017
Curso muy completo que da conocimiento realmente avanzado sobre modelos gráficos probabilísticos. Aviso, la especialización es complicada para los que no somos expertos del tema!
par Jorge C•
Sep 17, 2017
Sugerencia: Algunos de los ejemplos numéricos presentados en el curso podrían ir acompañados de alguna expresión matemática intermedia que facilite la comprensión de los mismos.
par Christopher M P•
Jan 16, 2020
Simply excellent. A wonderful course to begin the representation of PGM. Be advised.... this can get quite advanced. It's all about that Bayes, 'bout that Bayes.... no trouble.
par Christopher B•
Jul 17, 2017
learned a lot. lectures were easy to follow and the textbook was able to more fully explain things when I needed it. looking forward to the next course in the series.
par Anthony L•
Jul 20, 2019
Some parts are challenging enough in the PAs, if you are familiar with Matlab this course is a great opportunity to get familiar with PGMs and learn to handle these.
Mar 25, 2020
really great course! very clear and logical structure. I completed a graphical models course as part of my master's degree, and this really helped to consolidate it
par Prasid S•
Dec 08, 2016
Very well designed. There were areas here I struggled with the technical details and had to read up a lot to understand. The assignments are very well designed.
par Al F•
Mar 20, 2018
Excellent Course. Very Deep Material. I purchased the Text Book to allow for a deeper understanding and it made the course so much easier. Highly recommended
par Vivek G•
Apr 27, 2019
Great course. some programming assignments are tough (not too nicely worded and automatic grader can be a bit annoying) but all in all, great course
par Sureerat R•
Mar 02, 2018
This subject covered in this course is very helpful for me who interested in inference methods, machine learning, computer vision, and optimization.
par Angel G G•
Dec 12, 2019
Great course, I miss some programming assignments (I didn't do the "honors"), but the quizzes are already good to test your general understanding.
par Ayush T•
Aug 23, 2019
This course is really good. It is well organized and taught in the best way which really helped me to implement similar ideas for my projects.
par Valeriy Z•
Nov 14, 2017
This course gives a solid basis for the understanding of PGMs. Don't take it too fast. It takes some time to get used to all the concepts.
par Isaiah O M•
Mar 31, 2019
I found well structured contend of these rare probabilistic methods (Actually this is the only reasonable course in this approach online)