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Well-made course, but unfortunately there are tons of mistakes in the programming assignments - in the comments, formulas, even in the prepared code pieces.

The best course in the Deep Learning Specialization. Really good and well explained. There are some problems and mistakes in the problem assignments though.

Somes basics, tiny bit of theory, a bit of keras and insights for practical tasks. Some strage errors in notebook exercises makes it 2x time longer though.

Great course. The only tiny flaw is that the introduction to Tensorflow and Keras was a bit shallow so that I struggled a bit with programming these parts.

Instructive course with useful concepts. However, there were many more mistakes in the notebooks compared to the previous 4 courses in the specialization.

Awesome introduction, but feels like Andrew is a little bit rushing since it is the last course in the series, I dont feel it is as clear as other courses

The CNN course was better in this series of courses. This course is also good, but more content could be provided. Still the best small course out there.

Faced issues regarding assignment submissions. Otherwise, the course is perfect. Would upgrade my review to 5 stars if this issue seems to be fixed later

Es buen, algo extenso, pero suficiente para avanzar. Algo importante es actualizar los cursos con los nuevos algoritmos, al menos uno, por ejemplo BERT.

This course is quite challenging, but at least the concepts were well explained. Wished that Andrew and his team could conduct a crash course on Keras :)

A great intro to RNN, LSTM, GRU, Activation. Programming assignments are rather messy though (unlike those in the other courses of this specialisation).

Great course, I like the practical application and assignments discussed in this course , wish latest research papers were also discussed in the course,

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