This course introduces mainly about RNN, GRU and LSTM. Great assignments. 1 score off for the in-correction in assignments. 4.5 scores from me actually.

Great lectures, really well explained, assignments could request more from the trainee to devise the logic instead of having it already defined for him.

Good course, however I would like to have more Transformers application in the last part as well as some information regarding the fine tuning of them.

Thank you very much for all the work you have done. I have learned so many things... I will try to use this stuff in the coming months. Yours, Thierry

The course is really good, I would recommend it to anyone who wants to learn the subject, but it lacks support from the staff in the discussion forums.

Very good course. Some editing issues in the lectures and small issues with the programming exercises (outdated Keras instructions and documentation).

The lectures are excellent. The assignments are an extremely valid trace of significant deep learning application, while they lack a bit of challenge.

Gennerally structured well. The explanation about the position encoder weren't very clear for me so I found other videos on youtube that explain it.

As always, this course is great. however, for some reason this course is much more difficult then the others, and i feel as if it is packed too much.

Really good course, like the others. A bit too black box in some of the programming exercises, so I expect to struggle when developing my own models.

The videos are really informative and well structured. However, the exams felt like Keras tests. A detailed Keras tutorial would have been helpful.

It was great course,

I wish we have more speech recognition contents

Hope, you add new course a bit focus on audio/speech recognition etc

Thank you!

The only reason I'm not giving it a 5 is the course 5 week 4 coding assignment. See my comments in response to post by @marcus-waldman for detail

too much content and not much chance to exercise. I will suggest for more frequently and smaller programming assignments through out the course!

Awesome course. I got to learn about Sequence models(GRUs, RNNs, LSTM, Transformers...) and how they are used in today's exciting applications.

Outstanding course, but the end of it uses many architectures not fully explained (GRU and such). Incredible course and specialization, though!

Excellent course, but I would have liked to work on predictive maintenance examples leveraging RNN and LSTM networks. Big thanks to whole team.

The course is nicely designed and every topic is explained in a very lucid manner by Andrew Ng. Must be done as a beginner in sequence models.

Simplified content delivered in just the right way to give a perfect intuition of the complex concepts. Really enjoyed doing the whole course.

Great content, but Andrew often starts his phrases then restarts saying them. Audio could use some cleanup, then this course would be perfect!

Most optional assignments contain bugs/errors. Other than that, this is a great course, just as the 4 other courses in this specialist series.

I give 4 star because some fomulas are not correct! Though this course is really great. I can not understand why you made mistakes on fomulas.

Great materials and programming exercises. The programing exercise in week 4 could be improved for the more beginner-friendly style probably.

This one seemed to go through to quickly over the details especially with the word vectors and the LSTM, would have appreciated more examples

Very good course, though the assignments towards the end were a little too centered around Keras, which I personally don't care for very much