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).
創建者 Kervin P•
Jan 05, 2017
This is an amazing course, and taught by an extremely talented and accomplished professor. I believe it's a must for anyone in AI/ML or Statistical Inference. The problem is that you're essentially on your own the entire course. There isn't any community or TA help to speak off. And the project is done in Matlab, so you end up wrestling with Matlab or Octave instead of actually doing and learning. I still recommend the course, but that's only because the material is so extremely important.
創建者 Christos G•
Mar 09, 2018
Quite difficult, not much help in discussion forums, some assignmnents had insufficient supporting material and explanations, challenging overall, I thought at least 3-4 times to abandon it.
創建者 John E M•
Apr 01, 2018
Lectures were OK and quizzes and exams appropriately difficult. But Labs were pretty difficult especially lab 4 which I ended up surrendering on. This means I didn't do the accompanying quiz and gave up on the possibility of honors recognition as well.
While labs don't have to be as hand-holding as the DeepLearning class by Coursera, it would be nice to get more help and maybe not submit errors for the parts I haven't tackled yet when submitting (as DeepLearning and MachineLearning courses figured out how to do).
創建者 Michael G•
Feb 05, 2017
The support by the mentors could be much better. Because of the missing support I was not able to solve the assignments under Windows with Octave. I had to buy Matlab. (-2)
It seems to me that the course is very difficult to complete without additional sources. (-1)
Sep 29, 2016
The content seems to be excellent regarding "what" is presented. But sadly the sound quality is rather bad: Sounds like an age-old valve radio with A LOT of dropouts. And Professor Daphne is an agile and therefore less disciplined speaker which lessens the understandability of her speech in conjunction with the poor sound quality furthermore. Especially for me as a non-native foreign english speaker it is very hard to follow. And now I am at one point in the course, that is "Flow of Probalistic Influence", where she explains a concept without explaining what is meant with the used underlying notions "flow" and "influence" which makes me difficult to understand what is going on. That means in my point of view that the slides are not sufficiently prepared. Although I'm very interested in the topic I am asking myself after the first view videos if I should continue or drop because my cognitive capacitity is for me to worthful to use it for the decoding of badly prepared and presented material. Ok, my decision heuristic in such cases is "Use the hammer not the tweezers!". Therefore I have dropped. Please improve the state of this class from beta to release. Then I will come back.
創建者 Benjamin B•
Apr 12, 2018
Did not like how the concepts were introduced, it felt like learning theory for the sake of theory.
創建者 Ashok S•
Mar 30, 2018
It is hard to follow the course without a book, and the book is expensive.
創建者 Alexey G•
Nov 06, 2016
It is impossible to submit quizes and programming assignments without purchasing the course. In my view this defies the goal of Coursera to provide accessible education anywhere in the world!
創建者 Casey C•
Nov 01, 2016
Superficial coverage of quiz and final exam material in the video lectures. Without getting the textbook and reading it in depth, it is difficult to do well in this class.
Jun 24, 2017
Lectures are awful.
創建者 Belal M•
Sep 08, 2017
A very dry course.