The assignments are not challenging enough. The concepts are really well explained and for someone with no background in this area, this is a great learning asset

Very good course that teaches you basics of convolutions, augmentation, transfer learning. Thank you to Mr. Moroney and the Coursera team for making it available.

The course was good. The only problem was the last assignment where some of the functions went missing. It was difficult for a beginner to catch such glitch

The best course to do. Especially after the specialization course from Andrew. It is really helpful to code all the concepts you learned from Andrew course.

I think most much of the course conent was same as the first course, this course could have been a little more advanced. But overall a great place to start.

Very nice the step from the first course was really nice. The achievements were harder to reach an all over the cose was less buggy than the first one. :)

Last coding assignment was not clear. Eg- Why is there a model.evaluate line at the end when we are already checking validation accuracy in fit generator

The contents are a bit light from my point of view. I get it is to be accessible for more people but math and explanations are in some cases important

it was great course but I need some more details and the speaking was a little difficult as some of words are slang and the translation was so bad

The course content was quite good and overall understandable but the exercises and quizzes were quite easy, they could have been more challenging

The hand sign assignment need more explanation about using flow object from ImageDataGenerator since I just know only flow_from_directory object

Learn a lot for CNN in this course, but require advance knowledge in Python & Numpy to understand the code as it was not explain in the course.

Exercise_4_Multi_class_classifier_Question-FINAL has problem if you entirely follow the tips, you can find the correct code in the forums.

Very nice and interesting videos, cool concepts, amazing datasets. Exercises lack sometimes clear objectives, or provide unclear feedbacks

I guess one thing was not studied, the method .flow() which get the images generated by keras with the dataset labeled for the final test.

The tutorials were easy to follow and I think the assignments were nice because some parts were easy, but some parts had some challenges.

Lectures videos are amazing but the only problem in programming assignments. Programming assignments should have been properly designed..

More detail videos or links,examples for important techniques like dropouts and for like multi class classification which may be optional

Content was great. It was insightful. However I felt, in few assignments, the instructions were misleading and took some to figure out.

The course is very useful for practical purposes. But this course didn't cover some advanced topics such as object detection and GAN.

Very good course to get you started on convolutional neural networks. Week two had a small problem with the programming assignment.

very practical courses on implementation of CNN in tensorflow. Suggest student also take the deeplearning series with this series.

Programming assignments could have been better. The programming assignments at the end of each week were not challenging enough.

This course offers more executable functions than actually helping you understand (in-depth) how neural network really works.

Good content and Lawrences technique was great. But it took a bit longer where assistance was required during assignments.