Too much similar material to the prior course, and only two simple quizzes, no hands-on programming assignments like in earlier courses.

A fundamentally very good course with a few technical gltiches that can be easily corrected and some confusing elements to be clarified.

I think this lecture is important for every research scientist. However, there was no programming examples so I was confused sometimes.

No programming assignments or labs, so too much theory, and too little chance to put same into practice. Not a good value for my money.

Still good but getting much sloppier. Bad editing of the videos, some exercises plain wrong and staff not reacting to forum posts, etc.

This session might not be very helpful for people from different backgrounds such as non-industral level application of deep learning.

Course materials need some cleanup. Were a number of audio blips, in the video. Material was good but just didn't seem as polished.

Decent learning. Though quite some stuff, I felt as repetitive and obvious.

I wish there was some programming exposure as well here

Too short on its own (took half a day to go through the whole thing), could have been combined with Course 2 of the specialization.

- could have been better with more hands-on excerices or assignments.

- the assignments were quite hard compared to the lectures

I feel like this course should be broken down and included in the other courses to get better context within these other courses.

this session was good it would be more better if they provided the code of them..so that we could be abke to learn more from them

Felt a bit rushed, each video was full of good tips but personally I think each video should have been a jupyternotebook instead.

More theoretical than the other courses in the specialisation but still very high quality.

Short but with a lot of information.

Not nearly as good as the first two courses. These two weeks should probably be added into the second course at some point...

Would like more applied discussion and for it to be Longer. In particular I would like to see a discussion on class imbalance.

The content of this course is a bit too little for me.

However, it provides useful guidance for my projects. Much appreciated!

Not nearly as valuable as the first Deep Learning course. And the questions posed in the quizzes seemed far more subjective.

Programming practices with TensorFlow should have continued in this course. Unfortunately, these two weeks were all talking.

Need more quizzes, assignments to deepen the understanding, But otherwise thank you Andrew Ng for presenting this material

The pace of the first part of the course was too slow. The second part (from Transfer learning onwards) was much better.

This course does discuss interesting and important subjects but I feel it can be combined with course 2 of this series

course is very good have a lot of important theory, it will be amazing if become 3 weeks with programming assignments.

lot of issues with assignments and ambiguous quiz questions this time around, not as polished as other Andrew courses

Could have more case studies and above all. Also programing assignments on self driving car could have been better