The video lectures are very good at outlining the concepts. The programming assignments with the jupyter notebooks are nicely done, but they do not go into much depth. Hence, the course mainly gives you theoretical knowledge than practical experience.

This one proved to be the most challenging for me in the specialization, especially the programming assignments. While the concepts are very very well explained by Andrew, the application (though well guided) required more trial and error on my end.

I really liked the course but there are many tiny errors in some of the videos, which they have fixed in a following article but I got stuck in a couple videos because of those errors and later saw the article. Otherwise the course is really nice.

Presentation of material is fantastic, but there were A LOT of technical problems with the grader that led to a lot of wasted time and frustration. Very good course, but please work to update the grader issues so future offerings are less buggy!

This course, out of all of them, seemed to have the most grader issues. Several times I had functional code with the right answers, but it got marked wrong and I had to hunt through the discussion boards to find out how to do it the "right way".

Excellent Course content and very aptly put tutorials .Course completetion is just a milestone and You keep going again and again these materials (even though you have gained certificate )you will learn something new. Thanks for this series !!

Great course, but some discrepancy between face recognition/verification notebook and the grader make this impossible to get full grade (I had to check in the forum and enter an answer giving a result not corresponding to the expected output).

I really wish they didn't provide so much boiler-plate code. It seems to detract from understanding the programming assignments fully. Yes, building the whole thing yourself would take 2-3 times more effort, but the end result would be better.

Tensorflow tutorial is too short. Although i finished this course, i still dont know how to use tensorflow to build my own nn and how tensorflow actually works. This course need update the tensorflow to v2, and provide more in-depth content.

Very nice course about a special type of Neural Network.

The course materials are really good as well as the teaching style of Andrew.

The only minor point is that the programming exercises are too easy with only "fil in the gap" challenge.

The course is good. Well explained.

The videos need some editing, sometimes speech is repeated which doesn't help with concentration.

Also, the forums need fixing, for someone used to Stack Overflow (and others) the forums work really bad.

Need more quick help from discussion forum since it is very important to understand the usage and working of components in the code. The course is superb in theoretical part but I felt I needed more assistance in programming exercises.

The contents are good, however the exercises includes too many errors and it takes too much time to read all the discussions to find out what the hack is. You should make sure the exercises are working smoothly before you publish them.

Since I have a computer vision background I was expecting much more challenges at this points when doing the pratical assignments. The explanations and intuititions about ConvNets are awesome , and this why I am giving 4 instead of 3.

programming skills by using tensorflow and Keras are required, and learned a lot of sophisticate program structure in this tough course. Worthy! Appreciated highly, but hopefully taking programming skills before starting this course.

really very good course with deep knowledge of deep learning backend but some extra content and work should to added to labs for elaborated explanation and practice.

some topics like how to select model model desining were missing.

Provide useful information in convolutional neural network and its application in image processing. However, there are many issues in the assignment and grading systems. Hope that these issues will be totally fixed in the future.

The grader in the final assignment was giving some problems even if the answer was as close as last decimal digit.Else the course was excellent ,it gave excellent insights to different architectures used in CNNS and its working.

Course content was really upto the mark with the current trends in convolutional neural networks, its the best choice for those with pre-gained knowledge about machine learning and have and idea of updating their skills in cnn.

As usual, the content is top quality. I did however notice several times in the recordings where Andrew tried to state something one way and then went back and restated the same thing - it seems like this should be edited out...

Really nice course of convnets. I think the intuition behind them could be more explained. In my opinion, the artistic part of the this nets should not be in this course as there is plenty of more important knowledge to adquire.

Thanks. Great course :)

There're some mistakes in assigments. Check the course forum when you're in trouble. The course forum is very helpful. Thank all the students and TAs who post their questions and solutions in course forum.

A very good course, but probably the weakest of those so far in the Deep Learning specialisation. Got better towards the end, but the first couple of weeks felt like some topics were not fully explained in terms of relevance.

Good course but I would really recommend doing a deeper explanation on backprop of CNN's. Also I think the explanation of YOLO is not arranged well. ultimately it gets there but when it is first introduced a LOT is left out.

Great material, but there was a bug in the grading of the final problem. To work around the bug in the grader, everyone is modifying their program so it doesn't match the expected results but nonetheless will pass the grader.