Exellent course for first experience with convolutional networks. A few mistakes that seem frustrating at the time you are completing course really help to gain better overall understanding. Thanks a lot for good work all the involved people, stuff and mentors.

Perhaps the toughest course so far, Convolutional Neural Networks introduces us to computer vision. Professor Andrew explains complex, state-of-the-art cases where computer vision is being used today. Great programming assignments, great lectures, great course.

awesome course! the assignment is actually not just a piece of homework, it indeed a kind of guidance, give you detail step by step examples of how to code the learned algorithm. Thanks to the lecturer, didn't find any course more 'user-friendly' than this one.

Wow.. what Can I say? This was the toughest of the three previous but super happy to be in this journey.

I learned a lot and I am motivated more than anytime to immerse myself in this field. There is so much to learn. Thanks to all the people behind this course!

Excellent explanations of the theory and math behind the basics of CNN that anyone can understand easily. The assignments are also well designed in such a way that one could apply the theoretical knowledge gained to solve real time problems. Excellent course.

Again, excellent course from Andrew Ng! Made complex algorithms and concepts very clear! Got to know how CNN, Facial recognition and Object detection works. Reference to the literature paper will come handy in the future if one thought of diving deep into CNN.

Excellent course. Concepts very clearly described. Only improvement would be more Tensorflow and possibly Keras training. Yes, you can go elsewhere for this, but Andrew Ng is so good at explaining, I'd expect he'd do a better job!

Many thanks Mr Ng and team!!

This was the most fascinating course in the series. It is amazing how quickly new innovations like the YOLO algorithm have managed to reach mainstream within a couple of years. I would encourage all students to also supplement the learning from other sources.

Very nice coverage of of CNNs with excellent examples and content on intuition. I also greatly appreciate the efforts of the instructor - he really does care about teaching the course and helping students - it comes through in his lectures and presentations.

Excellent course ! Theory and practice are covered in a relevant way, and Andrew's been very encouraging and clear all along this CNN journey ! The fun part is obviously art generation with the VGG19. Great thanks to Andrew and to the deeplearning.ai team !

The course is pretty good with advanced techniques on computer vision. The only regret is one problem about the last coding homework. I failed to load the pre-trained model and can only finish the home work without checking the accuracy of designed examples.

Amazing course plan and delivery! Classic CNN architectures, ResNet, YOLO, face-recognition, neural-transfers - all in a very succinct package! Some very minor issues with auto-grading of assignments, but nothing that the discussion forums won't get you thru.

This was a great course for learning the nittigrities of several concepts including CNNs, object detection, face recognition, etc. The ideas were presented in a lucid manner and the programming exercises were a great addition to the overall learning process.

Really great course in this deep learning specialization. I have enjoyed the entire course. Video quality is high and the instructor, Andrew is really awesome, I couldn't express in my word. Thank you Coursera for giving me the chance to complete the course.

Andrew's explanations, and the exercises are absolutely fantastic. There seems to be a lot of tricky math in Convolution Neural Networks and Andrew's explanations and illustrations help students understand the essential concepts behind each type of Conv net.

Excellent course. Very good and well structured explanations by Andrew Ng: one concept per video, sometimes a second video to explain why the concept works or to give some intuition. Course covers many of the classis deep learning papers. Highly recommended.

Weeks 1 & 2 were very good. Week 4 was excellent with extremely clear presentation. I didn't like week 3; it felt like the topics were presented in random order, and the homework felt trivial (I finished it easily but I still have no idea what was going on).

Awesome, I loved taking this course, the way to explain the topics is the best. I enjoyed every part of this course and the most important part I understanded several concepts. The exercises and material class are really usefull. Congrats you're the best.

This course was the greatest one among the first 4 courses of the Deep Learning Specialization. Real world examples were perfect. Moreover, the paper suggestions helped me a lot to learn through my process of this course. Thank you Andrew and Coursera Team.

Great examples and walkthroughs. I didn't think I would be able to code all the various CNN architectures, but this course made that process challenging, but doable. Now it is time to start working on side projects to sharpen the skills I have learned here.

Probably the best course in the specialization (well, along with Sequence models). 50 layer VGG model built in Keras gives awesome enterprise-level results on a relatively small data sets..! But I recommend taking all these courses, they are all very good.

I really like how Andrew Ng is able to explain actually pretty complex concepts in a comprehensible way, built on the knowledge of the previous weeks content.

Also great is the integration of recent techniques: inception modules/networks, residual networks.

Excellent course. Professor Andrew Ng ensured easiness in following the courses, highlighted important aspects and the assignments were very well structured. I am glad to have taken up this course and I hope to start using my learning in the coming months

Amazing!! The assignments very well cover the concepts taught in video lectures and each part of the convolutional network is explained in detail. The First 2 weeks are quite full of concepts. I enjoyed the last 2 weeks covering the applications of CNNs.

Andrew Ng's courses and Geoffrey Hinton's are about as good as courses get--rigorous, practical, and yet fairly thorough in the underlying theory. Convolution Neural Networks is certainly no exception to that as he goes into res nets and inception nets.