Sep 02, 2019
This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.
Dec 12, 2019
Great Course Overall\n\nOne thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.
par Dipo D•
Jan 11, 2020
Like the other courses in the DeepLearing.ai certification, this course was also very crystal clear in teaching the concepts. Now, I can confidently read additional materials on Computer Vision. The assignments were also well thought out, kudos to all the TAs. Thanks for the awesome course.
par Rahuldeb D•
Sep 04, 2018
Another exceptional course offered by Coursera. There are lot of new concepts to learn in this course.
Prof. Andrew Ng has explained each and every concepts in very lucid manner. I want to give a big thanks to Andrew Ng and all other teaching associates for offering such a beautiful course.
par Brandon W•
Nov 24, 2017
Students had some technical issues throughout this course, with the autograder not correctly grading the assignments despite having all expected outputs correct. In time, I hope these issues can be fixed. However, given the level of instruction and quality of the course, still deserves a 5.
par Anoop P P•
Jun 10, 2020
The course has balanced of theoretical and practical aspects of Convolution neural network. Moreover, practical sessions encouraged to create a CNN from scratch, use a pre-trained model to fulfil the task. The assignments has helped to practice hands-on using tensorflow and Keras platform.
par Ajay S•
Aug 30, 2019
really a great course for the image learning . i love this course well . and thanks for providing me the financial aid for the course . this will really help me to complete my research work on time .
Thnaks. for the profession Andrew Ng . for the designing and teaching a wounderful course.
par HE Y•
Jun 24, 2020
I think this course offers an excellent illustration of convolutional neural network for beginners, even for those who have a basic knowledge about the neural network. The two applications of CNN are quite interesting and useful. I have learned a lot through this course and thanks Andrew!
par RUDRA P D•
Jun 20, 2020
Amzaing course on ConvNets but in my perspective anyone who wants to opt this course must have basic understanding how Tensorflow works and basic operations in it. Except every concept are well explained and also research papers are given (for who wants to dive deeper) in the assignments.
par Sean C•
Feb 20, 2018
Andrew Ng's explanation of Inception Networks greatly helped to demystify more complex-looking architecture diagrams in Google's Inception Net. This course helped a lot in being to be able to understand the base building blocks, as well as their arrangement & purposes within the network.
par Vincenzo M•
Nov 26, 2017
Another super course from Andrew Ng and his team. As the other courses of the specialization, it presents the core concepts clearly. The exercise are foundamental to retain the concepts. As a suggestions, I would substitute the style transfer with an example more useful for real problems.
par Chun-Huang L•
Mar 22, 2020
This course teaches CNN from the very beginning to the most details. Its examples and assignments are very impressive for people to know what happen in the model and how it works for many different applications. I can realize most CNN-related research papers after finishing this course.
par MOHD F•
Jul 23, 2019
Convolutional Neural Networks by Andrew Ng is a Great course to start into the of CNN's Terminology for DeepLearning. This course provides me with a solid background in how the Convolutional Neural Networks works internally. Great lectures ........... Great everything thankyou Coursera
par Rahul S•
Apr 30, 2020
This course gives you adequate foundation to build upon your knowledge in the subject. The structuring of course is perfect and assignments help to pick up difficult codes so easily. Andrew is an exceptional teacher who knows the field and shares his experience and knowledge so humbly.
par Miroslav M•
Apr 24, 2019
I've gained very important knowledge for Image verification and recognition algorithms using ConvNet models. These models are used nowadays powering robots and self-driving cars. Thank you very much deeplearning.ai for this opportunity to get closer to finishing my new carrier journey.
par Janzaib M•
May 06, 2018
Very very well designed homework. Gave me a really close feel of deep learning for computer vision. The great thing is, in this course you play with very very state of the ConvNet architechture. Thank you so much Professor Andrew NG and your team. A very big contribution you have done.
par Huang C H•
Nov 24, 2017
Convolutional Neural Network are exciting to learn, but its concept can be quite abstract. However the materials are delivered progressively, and in a concise manner. The programming exercises are challenging. I hope there was more in-depth introduction to Tensorflow and Keras, though.
par AKSHAY K C•
Mar 19, 2020
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.
par Feng W•
Mar 15, 2019
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.
par badreddine m•
Dec 24, 2017
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.
Feb 15, 2018
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.
par Wooshik K•
Feb 11, 2020
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.
par Sathiraju E•
Aug 05, 2019
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.
par Yernur N•
Jul 18, 2019
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.
par Matheesha A•
Jun 21, 2019
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.
par Ravi P B•
Apr 17, 2020
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.
par Xiaolong L•
Feb 05, 2020
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.