the programming assignments are well prepared and give you good understanding of how the thing really works. Also it doesn't require much effort and easily understood

This I s a great starting course on deep learning , ANdrew has helped the learner by structuring the course so nicely. this is so far the best course I have ever seen

Solid, methodical explanation of approach. Enough focus on practical examples and actual coding to make it easy to build on this introduction for actual applications.

The lessons are at the same time very detailed and wonderfully taught, the examples are clear and the quizzes/programming assignments adequate in terms of difficulty.

Best MOOC I have ever done! Such rich content. Challenging material. Great instructor. Good solid foundation for further courses in Neural Networks and Deep Learning.

Excellent course on Deep Learning basics. Andrew makes it easy to understand even if there's some maths involved.

Programming exercises could have been more difficult.

Very good course especially at teaching the theory of DL, though the projects could be in PyTorch instead of Tensorflow because Pytorch is the industry standard now.

Absolutely amazing course, it helped build my confidence for deep learning. beautifully sculpted course. Thank you Andrew sir, m soo happy that I joined this course.

Great orginization and presentation! Andrew Ng eases you into linear algebra, differential and partial differential equations, Can't emphasize on how much I learned.

A very good course with in depth explanation about the building blocks of deep neural networks and excellent programming assignments for a great learning experience.

Another awesome course of Andrew sir! Previously completed his Machine Learning course and that was as great as this. Thinking to complete all deep learning courses!

I've learnt a lot of new things. actually, I understand what is the logic and math behind deep learning. Thanks to Dr Andrew Ng and other instructors of this course.

Amazing course for those who wants to learn about Deep L layer networks. This course teaches from basic logistic regression, 2-layer NN and building L layer deep NN.

Excellent curriculum for CS background students with poor math knowledge. I would recommend it to any Software Engineers trying to become Machine Learning Engineer.

Great course for anyone who is either looking to refresh their understanding of NN or want to get a deeper understanding of NN before taking up more complex courses.

Although this course is a bit short in my opinion, the new notation and revised explanations are worthy of recognition. It is a very good course. HIghly recommended!

A VERY VERY THANKS FOR THE INSTRUCTOR FOR INSTRUCTING THE WHOLE TOPIC WITH SUCH A NICE GESTURE AND INSTRUCTING IN SUCH A WAY WHICH GIVES THE HANG OF IT VERY QUICKLY.

Excellent course in deep learning. I have learned a lot from this course, e.g., knowledge, coding, and application. All of these will help me in the future research.

I like the way you are training students/scholars/researchers and the tolls you are using like Step-by-Step learning using Notebooks. Assignments, discussion forums.

The low-level knowledge of how neural networks work has been very useful in understanding more complex examples. The ground-up approach taken by the course is novel.

Muy buen inicio para la especialización en deep learning. No puedo esperar para ver los siguientes cursos. La implementación de los Jupyter notebook es muy práctica.

Excellent course for beginners in the subject. I personally enjoyed doing the programming assignments of python which were really well made to enhance understanding.

Andrew Ng makes things very easy to understand! The course gives a decent overview of the neural network and practical coding home works helps to clear fundamentals.

This is a great practical introduction to deep learning. You will learn how deep learning algorithms work and you will learn how to build them in Python using Numpy.

Andrew Ng's style is so compelling and very easy to follow. The concepts explained in the course are structured in such a way that learning is a natural consequence.