That was much harder than the previous courses of the specialization. However it felt like the videos are more hasty and less understoodable

There was a bug in a programming assignment notebook that took too much time to notice that i was doing ok but the expected ouptut was wrong

The programming assignments required some extra effort to understand Keras which I thought may need an introduction video like tensorflow.

Several grader issues, only 3 weeks of work, and a lot of errors in the solutions... In addition, less content than in the other courses...

The earlier courses were easy to understand, however, this was way too difficult. Andrew Ng did not make this easy like the other courses.

Compared with previous courses, this one seems to be rushed. The focus on applications seems to be much higher than the theoretic side.

Not as great as the other courses in the specialisation. The assignments can be a little off putting, but lectures are top class again.

Week 1 took double time to be completed. Times proposed for the assingnement are underestimated.

Please readjust the assingement time.

Assignments are not up t the mark.. Expected to have high vocabulary size word embedding assignment, Machine Translation assignments

The theory part was great as always. Compared to the first 4 courses the labs were not that good and some of them very confusing.

This course was good but in comparison to the other courses in the deeplearning course series, this course lacked adequate depth.

The course is a good course because the lecture Ng.W ,but the exercises is not easy for our beginers for such tools like kears.

The programming assignments in this course are difficult to implement. The detail descriptions are needed inside the notebooks.

Good subject, but a lot of the course material (like lecture slides and problem sets) was either unavailable or out of date.

The videos are great - however it would be useful to provide some help on how to implement the concepts programatically.

The assignments need better instructions and there is a huge jump in complexity when going from lectures to assignments.

Not as good as the previous courses in the series, and some of the assignments where broken, and super hard to debug.

Last week's course about transformers was extremely rushed to the point I wasn't even able to get a solid intuition

Only on NLP applications, it would have been great to apply GRU or LSTM on numerical data like finance for example.

The content covered is interesting, but I feel like the explanations are not as intuitive as the previous 4 courses

Nice but little stressful. After completing 5 courses in a row, really feeling exhausted. Thanks for the good work.

Quite a lot of bugs in the first week examples. It took me too much time until I browsed the discussion forums.

the videos are programming assignments need some serious updates, too many typos and wrong information present

I think you have to know more keras than is explained in the course. The keras documentation it is not enough.

An average course, it is detailed though some of the ending materials get too difficult for me to comprehend.