Excellent course. Explained in a very basic & understandable way for those who don't want to be complicated with too much mathematical background and still refers the participants to optional reading materials + active discussion in the course forums.

Well designed exercise, in which I only need to read thru and understand the key points, and the actual coding part is very minimum. Courses are well taught with enough readings and reference provided. Most of them are up to date in research frontier.

Awesome Learning Experience. The topic itself is so much interesting and fun. With this course, not only I learned this amazing tool but also reminded about the sense of responsibility in using this tool. Thanks a lot for teaching the course.

Thank you all coursera, DeepLearning.AI, Slack Community Members. I get so many important knowledge and insights that will help to do my MSc. Thesis. my little suggestion is some module need more explanation for ML beginners. Thank You Again.

This course was awesome. All the concepts were up to point and all the detailed reading materials are provided. The notebook's configuration was perfect to train the model. Looking forward to the same experience in the next course.

Great explanation and great way to summarize huge topics but the assignments are really taking a huge time for training purpose if possible try to reduce the no.of epochs or provide a pre trained model and training the last layer

The course is very good.The video lectures were super cool to understand.I just felt that the assignments should be a little bit more difficult like it should be given to write most of the code rather than filling just some cells

Thanks much for the course. The contents are concise and optional material is called out separately. The speaker can slow down a bit as it's hard to keep pace understanding what she is saying and looking at the video contents.

this course is very good and very entertaining , I liked how the programming assignments let us play with gans, and the lecturer is quite skilled , the lecture slide were simple and minimalist and this is what i like to focus

Even though the lectures style is quite different from the previous deeplearning.ai courses (showing slides instead of explaining on a white-board), the Colabs made the understanding the concepts very visual and intuitive.

Very nice and informative introduction, even though it might be a bit difficult at times if you have never heard of concepts like "latent space" or "disentanglement" before :)

In all, really great work, thanks for this.

This course helped me understand the foundations of GANs. It's full of coding assignments & references to original papers introducing different architectures. It is a best choice if you're absolution beginner to GANs.

This course introduces concepts in a clear and simplified fashion and allows to have a hands on with basic GANs models. Further insight can be obtained through the recommended papers. I look forward to the next course

This is one of the most amazing and practical Deep Learning courses I have ever taken. This course dive deep into GAN and provide many notebooks and research papers for us to practice and explore. Thank you, Sharon.

I have been trying to understand and implement GANs for que a few weeks and it felt really hard but after this course made everything easy for me, deeplearning.ai has been really one of the best places to learn.

It would be helpful to include the formula of the normalization in the last parts of the assignment, as reading through the instruction is fine but having the actual regularization formula available is helpful.

Nicely explains intuition behind things to implement. Walks through from most basic GAN to better versions and what improvements needed. Notebooks are good, even beginners in PyTorch can learn. Recommended.

This course is a truly amazing course. It bridges theory and practice and makes GAN easier to understand. You can also learn neat implementation of GANs that follows best software engineering practices.

Wonderful course for anyone interested in getting an introduction to GANs. All this knowledge will help me get closer to do research on state-of-the-art GAN models. Thank you for creating this material.

Excellent course, the first good thing is using PyTorch, love it , never had work with this framework and its really nice, second thing is about GANs, amazing topic I really want to learn more about it!

Helped me clarify the some of key principles and theories behind GAN and bit of history... The references/additional study materials are very useful, if you want to dig deep into. Overall very pleased

Great introductory to GANs, focused on the building blocks to neural net/ GANs, and a bit of frequently used models. Might need a small update on what's considered "state-of-the-art" in the course.

Great introduction of GANs. I particularly liked the programming assignments' difficulty (not too easy and not too hard). Also, the instructor is usually very clear and didactic.

Very nice course to start your acquaintance with GANs. Loved the non-obvious mention of ProteinGANs to generate protein structures.

Definetly a recommendation for the novice.

The course is great with hands-on experiments. The assignments are properly designed to let the learner focus on the most important pieces of the logic in the implementation