I really enjoyed the course, but I think some of the responses from the mentors in the discussion forum leave some doubts.

It is a very interesting course. I just regret that no documentation can be download to use it as reference in the future.

The missing of practical exercises I think is a real disadvantage. Is always better to learn by practice than by theory.

Would be nicer if there are coding assignment that can guide us through some of the applications mentioned in the lecture

Good and useful content. The staff should read the forum's errata section and make a bunch of fixes to the course though.

Excellent course material would have been icing on the top if there were some course exercises like previous two courses.

I think some videos materials related to deep learning practice(programming assignment seems costly) will be more helpful

an interesting short course on some of the things to be careful of when carrying out/planning a machine learning project

Pretty quick and easy course, but there does seem to be some good content in there. Almost no technical content, though.

No coding exercises; only quizzes which lean slightly on trivia rather than core ideas. Nonetheless, a very good course!

Maybe a week with an actual applied transfer learning assignment would be useful? (In addition to the existing material)

The course is a bit too theoretical. Programming HW supporting iteration, error analysis will greatly help this course!

Nice course, it helps me more understand on structure of project and give some technique to plan project more effective

Batch Norm, Multi-task learning and transfer learning exercises were missing.

Flight simulator exercise was also missing

It was an amazing course that helped me better understand the practical organization and application of AI/ML projects

A very good course. In my opinion, I would have like to have more practical examples or more tests to prove yourself.

Good course and I was able to grasp some tactical and crucial factors governing the working of Deep Learning Models.

Slightly boring, but from an importance standpoint, this course covers a lot of concepts which help in the long run.

The content of the course is unique, but I think sometimes is not totally clear how to apply some concepts and when.

This course is good and give you skill of error analysis, as well as how to handle data from different distribution.

I think this course would be more valuable if I have more experience so I could fully understand what I've learned.

I appreciated the insight brought here from the real life projects, though the quizzes/assignments need more honing

Amazing course with an amazing mentor. He is now becoming one of my favorite mentors. Thank you so much Andrew Ng.

Some mistakes in the audio. Test questions from week 1, seemed like some of them came from the material in week 2?

this course is really helpful for an enthusiastic deep learning student.it will help one to design a good model.