there were bugs in the jupyter notebooks

programming assignments are not helpful

some of the quizzes were a little buggy

I did not like the assignments of w#4

The videos need to be edited properly.

Little bit hard programming Excercise

Too hard for someone new to tf.

Assignments can be made better

Need improvement on assignment

good for basic understanding

notebook were not functional

need improvement of content

Notebooks are a bit buggy

Serious bug in assignment

too many errors in test

Labs should be tougher

部分内容讲的不是很清楚，有些剪切不好，有重复

Very complex Subject

没有翻译 tenserflow也讲得不好

Not enough theory

too theoretical

too many bugs

so hard :(

It was okay. Andrew is obviously very knowledgeable, and there is a wealth of knowledge here. I could go through it a couple more times and still pick up new stuff.

That being said, I've heard him mention he did these videos at like 1 or 2 in the morning after work, and it's very obvious from the videos. He makes so many mistakes that every other lecture (it seems like) has a **CORRECTION** notification next to it. I mean it's great they give this additional correction information, but it would be even better if you just redid the video.

Furthermore, he like stops in the middle of the videos and then repeats the last sentence he said, because he made another mistake. I get it, Andrew is very successful, he's very busy, and I am definitely grateful for the knowledge he's provided in this course. But this makes for a very poor learning experience, because I'm taking notes, and I have to go back and redo them, plus the general angst you get when you're learning something and someone's like "oh wait nope that's not right, forget that." Well for God's sake I already learned it.

Finally, the submission assignments are the most annoying things I have ever come across. They are riddled with errors and misguided information where they literally tell you to use the wrong parameters, and then they never fix it. You have to go into the discussions to find out why your code is wrong, even though you're doing it right.

Then, you'll get everything right on your code for the test cases, and when you go to submit it fails you. And when I say it fails you, it gives you a literally 0 out of like 30 points. And the grader output just says "your submission was incorrect" like no way, I had no idea. Thank you for that very **cough** helpful piece of info.

If you go to the discussions, you find out this is actually a problem with how the grader is built, because if you don't format your code exactly the right way, it fails you, even if your solution is correct. I don't understand why it can be right when you run test cases, but submitting it fails.

Overall, I give it 3 stars before the poor grading, but because of the poor grading performance I have to bring it down to 2. I can't tell you how much time I wasted trying to figure out why my code was wrong just to realize it was right, but they screwed up their implementation.

In conclusion, this reminded me of a college course, where the professor has a ton of knowledge and is in high demand, and doesn't really care whether you get anything out of the course or not. It's sloppy, doesn't seem to be maintained very well, and most of the mentor's responses are literally "did you look at your colleagues similar questions?" Like no I didn't, that's why I'm asking. Why am I paying you so I can spend more time debugging your screw ups? Or maybe I did and I still don't get it because your explanations are ridiculously unclear.

I have one more course in this specialization and I absolutely can't wait for it to get over with so i can move on to more productive (and immersive, since these exercises are just one off "do this then do that" instructions, I still don't know how to set up a Deep Learning project from scratch) ways to learn Deep Learning. If Andrew wasn't so knowledgeable about this topic, I wouldn't even take it because it's that bad. But really you can't get this type of knowledge in such a condensed form anywhere else.

Hi! First of all, I love the specialization and these courses might be the best out there in DL (insane knowledge and Andrew is the best explaining, to be honest). Now, I have to give this 2/5 simply because of Coursera's side this last 7 days.

1. Last thursday, the 'Permission Denied' error -which affected hundreds of users- took over the Jupyter notebooks.

2. On friday, DeepLearning.ai mentors told us that you were aware of the issue and they offered us some 'hacks' or workarounds to actually progress while you solved the error. We were told to wait.

3. On the weekend -not a single official communication on Coursera's side yet (an email or something, the kind of thing a service does when their own product doesn't work, you know)- the mentors told us that you have already solved the issue (?). Of course it was not, and hundreds of users reported it again on the forums. We were told to wait.

4. The workarounds -given to us by the mentors- actually worked for some of the notebooks, but not for all. We were told to wait again.

5. After maybe a whole day inside the forums, we were told again that Coursera has solved the issue and the mentors told us that we needed to refresh the lab. Yeah, that worked... this is monday / tuesday by the way.

6. The issue was apparently solved, but yesterday -after following all instructions- i got a 0/100 grader (?). I contacted support (no solution). Solved by myself. On to the next assignment - Worked. On to the next... dead kernel... I contacted support two times (no solution and i was told to -AGAIN- go to the forums so another person could contact Coursera's support (?). Basically a black hole.

7. I've spent two hours now trying to submit my last assignment of Convolutional NN (yeah, dead kernel)

8. These past 6 days have been a waste of time, straight up. 6 days copying and pasting in an external text editor, 6 days with our attention on the blogs because, you know, 0 transparency on Coursera's side (yeah, its crazy to me that no official message was released).

Honestly, I was thinking of dropping out of the specialization if i couldn't submit the assignment today. Very disappointed with Coursera's communication and support