Nov 18, 2017
This course is little difficult. But I could find very helpful.\n\nAlso, I didn't find better course on Bayesian anywhere on the net. So I will recommend this if anyone wants to die into bayesian.
Jun 07, 2019
Excellent course! The perfect balance of clear and relevant material and challenging but reasonable exercises. My only critique would be that one of the lecturers sounds very sleepy.
par Daniel T•
Aug 06, 2019
The material is good and a lot of effort went into designing this course. Nonetheless, it feels neglected and could use an update.
The presentations are somewhat muddled by notational abuse. Indeed, it's customary to shorthand every distribution as "p" and let the arguments remind you which variable it came from, e.g, p(x|y) is conditional density of variable "X" at x given that "Y" = y. But then "p(a|b)" could be a completely different function corresponding to random variables "A" and "B"; however, you could have a=x and y=b as vectors which amplifies confusion... And when many variables with different ranges are involved and there's no consistency between labels for the variables and labels for their values, one has to spend extra time deciphering the material. Keeping track of the random variables and adopting a more suggestive notation would go a long way. Also, in Bayesian context it helps to avoid the word "parameter" (other than hyper-parameter, maybe), e.g., the weights "w" themselves are just values of a random variable, which is no different than the data generating process or the latent variables.
The programming assignments contain a lot of missing or inconsistent instructions. Be prepared to sift through the forums to find what is really expected or how to fix the issues in the supplied code.
Overall, I get the impression the course is now maintained by the students. It would be nice to see a revision from the instructors.
par hyunseung2 c•
Sep 19, 2019
Jan 16, 2019
Not structured well
par Gourab C•
Jun 26, 2018
I felt the explanations too mechanical and in between they skipped a lot of concepts and explanations.
par Luka N•
Nov 10, 2019
Too many probability concepts with too little examples and areas where one can apply them. Also, some steps in the computation are skipped which makes it harder for the learner to understand them. I spent hours trying to figure them out and get the result teachers have got on videos.
par Amith P•
Oct 28, 2017
doesn't explain many of essential concepts / theories. This course is mainly for those who has graduate or post-graduate level knowledge of statistics, who ironically may not need this course.
par Jae L•
May 13, 2018
difficult to follow unstructured lecture contents.
Nov 08, 2017
it seems that the prof didn't prepare the course well
par Lizbeth R P•
Jan 22, 2018
Maths are not easy but not impossible. However I find material not well prepared (defficient mathematical notation). Additionally, it takes a lot of time to get some help from the forums.
I encourage the instructors to revise the provided material.
par Vadim K•
Sep 11, 2018
Terrible task design.
No PyMC documentation provided
par Dizhao J•
Aug 08, 2018
very bad Interpretation