I would like to access the course assignments evene after I have completed them. So that I can use them for reference in future. Is it possible to make that happen or can i get the submitted jupyter notebooks mailed to me?

There were some little bugs in the grader, which was sometimes a bit frustrating, but overall I learned some super cool state of the art stuff and the explanations in the videos (maybe except for the YOLO) were very clear.

This is also a wonderful course in Data Specialization series. All the complexities of CNNs are presented in very intuitive and simple manner. The assignments were also very helpful. Thanks Coursera for bringing it to us!

A little bit more detail about the YOLO network like how the bounding boxes contribute to the training process and how it speeds up the iterating process would be very much appreciated.

Thank you for the wonderful course!

This one was the best course that I have done so far in the deep learning domain. I would recommend this course definitely if you want to learn from the conceptual background of CNN to its application in computer vision.

Excellent course on CNN concept, evolving architectures, and applications of classification, object detection, and image verification and recognition. Coding are fun. Student get to play with more packages and libraries.

for me, Andrew's comments were most valuable part of the course.

the exercises are just right for introduction and to encourage learning and progress towards completing the course while not getting bogged down with detail.

The course has a lot of good content and the programming assignments are interesting. The course actually describes the various architectures of CNN's and the reasoning behind them. It still has some video editing issues.

I learned a lot in this course. The course explains some papers in an easy-to-understand way. Really recommend it for those who wants to explore the world of deep learning. I learned a lot! Thank you deeplearning.ai team!

Great overview of basic CNN concepts and history, with pointers to relevant articles.

On the downside the automatic grader for some assignments was not set up correctly, which caused unnecessary time waste and frustration.

Absolutely amazing course. Highly informative an nice explanation about convolution operations and CNN algorithms. Recommended for all beginners and intermediate levels who really want to know something deeper about CNN.

Some kinks in the video cutting of Andrew when he makes mistakes, but otherwise very good course. Didn't know anything about convolutions before and am fairly confident in my ability to at least read papers about it now!

My favorite course in the specialization! Each week of lecture builds on the material covered in prior weeks. 8 programming assignments and quizes reinforce what is taught in lecture. Thank you so much to the DLAI team!

This is a great introductory course for anyone who is new to the world of conv nets. Andrew gives excellent intuitions about the concepts , which helped me to have a deeper understanding about the convloutional networks

I really enjoyed learning online course on Convolutional neural network. Thanks for the great instructors for having made such a great learning content keeping in pace with the recent research papers in CNN.

Thank you.

Discussion and reading on existing CNN architectures/frameworks was very interesting. Got to know a whole new collection of research and implementation in the field of CNN. And as always, Andrew NG is wonderful teacher.

The most challenging to date - but clearly expected. This course is fascinating and demonstrates the true power of Deep Learning with respect to things like Facial Recognition and Neural Style Transfer. Amazing stuff!

That's what I came here for! Lots of applications on convolutional neural networks, with many ideas explained. As usual, I wished he would give us a little bit more details, but this is anyway a really brilliant course.

Best course I've ever taken on CNN's. I now feel confident to attempt building computer vision applications of my own. Thank you to everyone at the deeplearning.ai and Coursera teams for making this material accessible!

I'm on week 3 right now and have completed previous 3 courses. I'm loving it very much, assignments are proving to be very helpful as you have simplified the process by providing markdown comments :) Thank you soo much

very informative i liked the learning style very much despite the system bug in garding i gave 5 stars because i encourge this Prof Andrew and his fellows to keep on the good work and provide more courses in the future

Fantastic course. I found the course material for CNNs and their applications to 1d and 3d models fascinating. The projects were challenging and informative. I am looking forward to the next course with RNNs and LSTMs!

The best course to learn traditional CNNs for absolute beginners. In the mean time, I think adding more recent research on CNN can make this course even better. E.g., vision transformer has been a game changer in CNN.

The best course (at least of the four courses that I have already taken) in the Deep Learning Specialization. The topics are perfectly explained. The only problem is that the final assignment has a bug in the testing.

Like the pervious courses, Convolutional Neural Networks is very useful to get you in touch with the new upcoming neural networks architectures. I particularly enjoyed the last course on triple loss and neural style.