the descriptions of homeworks are sometimes ambiguous, students may spend too much time trying to understand. Also, I strongly recommend teachers can interactive with the PPT when lecturing, instead of reading the draft directly.

Pros:

-thorough course material

-ambitious and interesting assignments

Cons:

-there isn't ANY assistance from the instructors or the TA. If you check TAs then you'll see that all of them written 0 posts on the forum.

-most assignments are severely underspecified. This makes them much harder than they should be, and it makes students spend hours on minutiae of preprocessing instead of more important stuff.

Lecturer had a difficult accent to understand. Briefly put up formulas and graphs but didn't explain them. No examples were worked through yet the quiz required this to be done. To understand this subject I will have to go away and study this from another source before I can understand it.

Worst presentation ever! Hard to follow, he reads from a text with no explanation. The worst! I also have to read the transcript to understand what he is saying.

Slides are not available, only the videos. Quiz questions are very unclear and ambiguous. Assignments have almost no direction and require many hours of commitment. Requires a significant amount of prior knowledge before taking this course. Would not recommend. Andrew Ng's deeplearning.ai specialization is much better.

Pros:

- excellent and challenging exercises

- relevant topics

Cons:

- poor feedback and course management

- lectures that do not teach you anything, it is more a taxonomy of what exists out there than explanation of anything

Some good topics and interesting homeworks, however, the lectures are rushed through without much explanation or examples, and there are many frustrating mistakes that belie the fact that this course is apparently not maintained and there is no support for students on the forums. Could be really good, but it's not there yet.

Nice introductory course. It include many background knowledge of computer vision before deeplearning and is important to know.

Lectures are good (mostly). But home assignments are very bad. Some links for datasets are broken. Admins did not fix it after a month (I found a message about it on the forum)!!! There are a lot of mistakes in a code. So, I spent a huge amount of time just for fixing bugs. It was very painful.

I think, administrators should read comments sometimes and update repos.

Some home assignments are very cool. But, mostly it is not possible to run it on a low-class laptop.

Moreover, there are a lot of mistakes in quizzes that was not fixed for a long time! So, people tried a grid search for answers. I definetely recommend to administration start fixing this bugs. This course is very good, but all this bugs discourage any desire to pass it.

Very poor instructions in course, can' even understand a thing.

1.Tutor does not explain clearly what exactly is happening, just reads the formula on screen as it is.

2.What is kernel and why we use it. Also what happens exactly when we convolutionalize,image matrix. Nothingggg is explained.

3. How one should solve the maths in graded assignments, when can't even understand the math behind the technique.

4. Speaking accent of tutor is very bad, can't understand if captions are not enabled.

I have taken many courses on coursera, which were very informative and in-depth explanation, but this course is just like National research university has nothing to do with if students are actually learning or not. It is more like earning money only.

There are several other cons which I have not mentioned.Very very disappointed.