Learner Reviews & Feedback for Build Basic Generative Adversarial Networks (GANs) by DeepLearning.AI
About the Course
Top reviews
great course, only teaching what's needed, doesn't push you a lot in the coding assignments, as much as it requires you much more work to understand the codes and the science behind it.
Excellent course. The videos were a pleasure to watch, the assignments were clear and allowed you to go as shallow or as in depth as you desired, and the mentors were very helpful.
176 - 200 of 257 Reviews for Build Basic Generative Adversarial Networks (GANs)
By makoto n
•ものすごく勉強になりました！いつもありがとうございます！
By Shoumik S C
•Sharon is a great teacher!
By Cường N N
•a Very interesting course
By ahmed h
•very interesting course
By amadou d
•Excellent. Thank YOU!!
By Natasha D
•Great course on GANs!
By Duy Đ
•Very helpfull for me
By Ji Y R
•Really instructive!
By Kshitiz R
•Excellent Course!!!
By Luis M C S
•hard but worth it
By Josue D G P
•Excelente curso.
By Robin S
•Truly brilliant
By Md A R
•Amazing Course
By Wildson B B L
•Great course!
By Victor d l C
•Excellent!!!!
By Irving G B P
•Amazing work
By Lâm Đ A
•Good course
By Andrew C
•Loved it.
By Hoang C V
•great !!
By Maciej A
•Awesome!
By Nancy A A
•Thanks
By jiangli
•nice
By Martin J
•An excellent course to bring one up to speed with current developments in GANs. Quite a bit of reading around the subject, in addition to the references provided, is necessary, particularly if you are new to using pytorch or python. But the accompanying Slack support is a life line.
I think this course is even more effective if you have the basics and want to review your state of knowledge and get a bit deeper in to the subject. Otherwise (particularly if you are fitting this in to your other activities), regard the time estimates for the assignments as wildly optimistic: multiply by 150% and use the next highter time unit.
But don't let that put you off, GANs aren't easy whichever way you look at them (unless you invented them)
By Daniel Y
•This is generally a good course to take. However, compare to the Deep Learning Specialization, there are few lacking points. First, the course touches only high-level concepts, which is good in some point but I expected more low-level as well. Second, Sharon speaks way too fast. Later in the course, I set the speed as 0.75x and it was better. I feel like Andrew spoke little slow in Deep Learning courses and now I feel slower is better than fast. Lastly, I hope that the course offers ppt slides available so that we can refer to it later. Moreover, some slow handwriting interaction would be good (like Andrew).
By AhmedAbdel-Aal
•The course is a great introduction to GANs. The explanation was simple and to point and the slides are great with the key points in the first few seconds and also with the summary at the end. However, there are some points that I did not like throughout the course. 1- some concepts that need to be well disgusted are just thrown in a 2 min video, and no matter how I repeat that video, I still can't get it because it is not so intuitive, so some points need more explanation ex: Wasserstein loss. 2- The assignments were not so helpful, I guess you should let the learner to code more than that.
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