Excellent lectures, terrible exercise material. E.g. "You're implementing how to train a model! But we've done the actual training for you already! Your exercise is to add numbers A and B! Number A is 4. Number B is 11! Enter A + B in the box below!" Also, someone did a search-and-replace and converted every sentence into an individual bullet point to reduce readability.

Unfortunately, this course is the less valuable in the specialization. Programming assignment very interesting but no introduction to Keras. To pass the assignments, forum support has been vital. I also found lectures not clear even to the point that to catch some concepts you have to google around for more resources. Unfortunately, I could not suggest this course.

Compared to the other courses in the specialization, this appears to lack depth and clarity one could expect. LSTMs and GRUs are somewhat out-dated now, given the speed of innovation in the field, and Transformers are here to stay (for now). Unfortunately, Transformers are very poorly covered.

Getting the input parameters correct for the Keras assignments is on par with the satisfaction of dropping a ring, contact lens, or an expensive object into the sink, and spending an hour looking for it inside the disassembled pipes, through built up hair debris and molded dirt.

Overall a great course, thanks to Andrew NG for his great explanations. But a very bad support, I faced many issues in submitting the assignment due to technical issues (notebook not saving) but no dedicated resource to help me. I spend lot of time in resolving my self.

Feels again like authors tried to put everything into just a couple of weeks, thus the course turned out to be messy with lots of details hidden. Even though there was a lot to learn, I am still not sure if I understand correctly how to build a simple sequence model.

Really good to understand the basics, however, it doesn't use the latest TF2 and the exercises are either trivial because too much pre-worked, or too hard because it doesn't give the information required to succeed.

This course really needs to be updated.

Programming assignment instructions are not well written (clear), and as a result it is easy to get stuck on something of little relevance to deep learning. Also, I would suggest that you make the lecture notes in written format available.

Assigments are pretty bad. I think in CNN and in RNN we should focus more on fundementals and build everything in numpy. RNN course isnt for building intuintion(deep knowledge) you just scratch surface.

The lectures cover the basic design of the models but don't help teaching you how to actually use them. I learned more by reading blogs to get the programming assignments to work then this course.

week 4 is a disaster as it skips so much details and motivation of why things are done in certain way. I strongly recommend the organizer of the course redo the video to make it easier to follow.

Lectures/Videos were excellent, the assignments were very poor (loads of errors in the code not corrected over 7 months since the course went live)

The course videos were very lengthy and difficult to follow. Many topics discussed in course video were not part of programming assignment

Good introduction to the concepts. Really poor quality videos and exercises. Very frustrating when working on the assignments.

The videos were very helpful but the programming assignments were way too easy for this certificate to be worth much.

Good lectures. Programming assignments are useless fill-in-the-blank exercises, you don't really learn much from them.

5 stars for lecture videos. -1 star for the terrible transformer programming assignment which is simply frustrating.

The programming assignments really are like pulling teeth. There's not really enough guidance leading up to them.

The course videos and the programming assignments were lacking. And there was no support in the forums.

Spent more time trying to work around a buggy grader than learning the underlying concepts.

Too hard to understand compared to the previous coursed in this specification.

Tough to comprehend. A little bit of written explanation might have helped.

Was very difficult. please add more expiation of mathematical equations.

Little unsatisfied with the final part of the specialization.

assignments are very hard and needs lots and lots of search