Very glad I took this course! A little rough around the edges as far as video / assignment quality, but seeing that this is the very first run of this course, I know it will only improve.

The material was great. Some of the programming assignments ramped up in difficulty or lack of perfect execution. However, I still gained extremely valuable information from this course.

The lecture for Sequence model was good motivation to get interesting about text and audio processing. All of lectures were very fundamental and intuitive. Thank you very much. Prof. Ng.

Very good and fun course in the sequence. However, it would be very nice if there were some examples of using RNN for things such as self driving etc, outside the realm of speech and NLP

The course videos are very good. However the optional parts of assignments have lots of issues and errors. Please update the assignment to reduce the time wasted unnecessarily debugging.

Very interesting exercice and assignments from which a lot is to learn. Content quite complicated which will require from me to come back for review and deepen some points. Thank you !

It was necessary to study extensively the Keras framework to fulfill the code tasks. I suggest an extra module with small simple RNN modeling exercises to better adapt the framework.

Overall, I really like this module. One possible improvement might be providing more information for backpropagation. Maybe as an optional video or just reading materials. Thank you.

nice course even few chapters could be more detailled technically speaking. However the assignements are very nice and helps to complete the understanding. Many thanks for such work

Thank you Andrew Ng for making me comfortable with the deep learning topics on Sequential data...Assessments were interesting ..can be made to enable us better play with the models

Week 2 was wonderful to learn and understand. I wish to explore more on LSTM and Attention based models. Video lectures were not enough for me. Still I am happy for what I learnt.

Overall it is a good course. Much need to improve on the feedback of grading of which output is not really helping. Referring to global variables in assignments are really tricky.

Overall a very good course , i wish the model construction ( i.e. the rationale in stacking up the layers) is covered in bit more detail, otherwise an excellent course, no doubt.

The assignments can be made a little difficult. Can Include assignments of Image captioning, that would have been great. Overall a great course. Sir Andrew Ng, superb teaching!!

great course as always by andrew. would give it a 5/5 but had some sloppy mistakes regarding the formulas. overal impression : exceptional and highly recommended. thanks andrew!

Compared to the previous courses, this one was a little hard for me. Because Dr. Andrew tried to squeezed a bunch of information in this course. It's a wonderful course though.

Some of the assignments are very difficult to pass. I think I understand the concepts but the instructions for the assignments could be a lot clearer and provide more guidance.

The course is great. The assignment sessions are a little confusing. It would be good to show the complete codes for the test cases so that test errors can be easier to debug.

I did not feel like I got a super clear understanding on how to use various library functions in keras, I did gain a really good understanding of the underlying models though!

Great course overall with lots of technical details. Week 4 content on transformers is high-level and makes it difficult and time-consuming to complete the hands-on exercise.

Excellent content, although the exercises - at this stage of specialization - should focus more on NN architecture, than on pure computational and matrix slicing tasks, imho.

Even though it has some flaws in audio clips and homeworks, programming assignments are fun to do. Great real world applications on this whole specialization is just perfect!

The content was quite good as with previous courses in this specialization. Just dropping a star because week 1 material wasn't as clear to follow as the rest of the content.

Compared to the first two sections, I don't think this section is better than those. Anyway, I learnt some concepts about sequence models which I need to dive into in future

A great course on NLP including Transformers. One star down for quite a brief introduction to transformers (I understand that time passes but you better update the course)