The course had a very clear outline starting from the basic fundamentals of CNN and progressing steadily towards the applications ranging from facial recognition to neural style transfer in the final week. Kudos to the instructor and his team for delivering such an outstanding course.

I have some problem doing week four programming assignment "Happy House Face Verification/Recognition". The pre-trained model "FRmodel" wouldn't be loaded (waiting for over half hour). I still managed to submit the assignment and passed the test without running out the correct result.

it is my second courses in coursera after Machine learning by Andrew Ng and Stanford university, I'm very satisfied by the courses quality and encourage you to go further, I'm a follower of coursera courses and one day I will contribute to share more knowledge using coursera platform.

i think that's the most important course for me, of course all of them, where very very useful, but being an undergraduate Robotics engineer, the most essential thing is to learn image processing and how to make your robot think and learn and detect object and learn from environment.

CNN is the topic that I love the most in Deep Learning, especially the role it plays in computer vision. I am so grateful for I am able to find this learning source on such a wonderful platform, helping me having a firm foundation and understanding on every aspect of CNN. Thank you.

Thank you for the lecture contents and programming problems. I am quite sure that I have acquired much knowledge and it will be very helpful to solve my own problems. Also, it would be much more helpful if there are some comments on how to build filter coefficients or filter banks.

Amazing course. A lot of knowledge packaged into one package. This has been the most useful course in the deeplearning.ai. Thank you Andrew and team. Lot's of interesting stuff and knowledge has been shared out here. Only the back propagation for CNN was missing but otherwise great.

It is an essential course for those who wants to boost their general knowledge in the area of CNNs. It will give you a great foundation to build on your career and further learning. I struggled a bit with Keras, but I am planning on taking another course to learn this field further.

This is an excellent course to learn the concepts of Convolutional Neural Nets. The hands on experience by the weekly assignments were very helpful to understand the concepts. I strongly recommend this course for the students who are interested in learning CNNs. Thanks Prof. Andrew.

A very detailed and pleasing insight into the amazing world of Convolutional Neural Networks and as always Andrew Sir has been absolutely brilliant in the lectures.This course presents an in depth knowledge of the challenges and various technologies in the field of computer vision.

Excellent course! The programing exercises are both realistic and let you build (toy version) of state of art CV system. Many reference to heavy weight papers in the domain in the course, which student who really want to get into DL and CV can read and further expand their horizon.

I got thrilled by the lectures and its assignments. One thing that I would request is a lecture on how to use pre-computed models, in all the assignments we are using pre-computed models. Andrew explains why we should use them but in practice its seems little difficult to use them.

This course is inspiring & really good. It presents with real research in a very lucid and simple manner.

I really liked the explanation of YOLO algorithm, was fascinated by it. With just one course to complete I am becoming fan of Andrew Ng and also other heroes of deep learning!!

Very Helpful for me! Andrew combine basic knowledge on ConvNet with advance architecture and application. The course assignments, lectures are all good.

I will choose Coursera my first Choice, as it will give financial aid too. Thanks for the instructor to making such good course.

Very informative course . Professor Andrew Ng has done a great job of explaining most of the concepts of CNN. And Assignments are really good to apply what we learn in the lectures. Professor Andrew is the best professor I ever came across the style of his teaching is unmatchable.

This is a very detailed introduction to ConvNet with descriptions of some modern ConvNet architect. Though I feel that if the programming assignment could be much better if we can implement some of these algorithms from scratch with efficient implementation (using Google Colab?).

Prior to this course, I have been thru so many other elearning about the exact same topics, but none have them gave such a crystal ,clear, and easy to understand explanation. It is very enjoyable learning journey. Thank you, Andrew and the content team for such a wonderful jobs!

Learned some really exciting stuff. It was great to learn a lot of the classical networks like resnet etc. Although, I wish the programming exercises did not have most of the stuff already filled in (though I understand it is done to make it easy for beginners to complete them).

The material is clearly explained by Andrew Ng in his calm yet enthusiastic style. Programming exercises are well structured and explained: if anything I find there's too much hand-holding but having got the basics, there's nothing to stop you experimenting further on your own.

Great course, concisely conveys both techniques and advice for practical implementation of Neural Networks in Image recognition. Great for a person who is already familiar with the idea of Deep Learning and want to take it forward, and ties in perfectly with the specialisation.

This course is a perfect way to teach these high-level concepts. They made it easy, step by step, and practical. You can learn not only convolutional neural networks in both conceptual and practical way, but also a lot of tips and tricks about tensorflow, Keras and even python.

one of the best fundamental courses that I ever attended, this course will build the basic knowledge for CNN and computer vision, and will help those who wanted to start a career in computer vision

for me, I was really happy during learning object detection and YOLO algorithm

Really amazing to get access to state-of-the-art deep learning science (and art) ! A right mix of general information, science and practice, together with the references to the articles describing precisely the technicity of what we discover ! Thanks so much to all the team.

This course is well organized and as someone with an intermediate level of experience with computer vision, I find this course very interesting and insightful. I really do recommend taking this course whether you're a beginner or a professional. Thanks for making this course.

The course is well structured, especially the exercise where one has to code the complete CNN example. It gives good insights on how to use the frameworks such as TensorFlow and Keras. Feel comfortable in understanding the concepts around CNN and it's implementation using TF.