Fantastic course. Started out to improve my knowledge for future projects and turned out to be eager to start the next lesson every time.

Explaining the basis of Neural Networks from its mathematical equations all the way to its Python implementation made this course the most complete I have ever had the pleasure to attend.

Andrew is an excellent instructor. The course gives the necessary essence of deep neural nets and covers all important topics to build your deep network. I am very happy that I decided to take that course. Its one of the most important courses I have ever taken. Thank you Andrew and coursera for offering this great course.

Recomiendo este curso a todos aquellos que quieran iniciarse en el aprendizaje supervisado utilizando redes neuronales. Sólo necesitas saber un poco de álgebra matricial y python. Y si tienes los oídos tan duros como yo con el inglés, con ayuda de los subtítulos ( en inglés también) puedes llegar a enterarte perfectamente.

Excellent introduction to neural networks and deep learning. As usual Andrew explains the material in a clear and concise way, with the right amount of mathematical derivations. The assignments are very well prepared and are extremely helpful in strengthening the theoretical preparation of the lectures. Highly recommended.

This is the best course for learning and implementing deep neural networks.It's really fascinating to see how the teaching material has been made and arranged. The assignments are so resourceful and still easy to understand because of documentation provided with every code snippet.

Thank you Coursera for making it possible!

An excellent introduction to neural networks. The concepts are very well explained with enough of the mathematics behind NNs to demystify everything.

Anyone who's done Professor Ng's Machine Learning course will find some material repetitive. But it is still worth doing some notation and approaches have changed quite a bit!

Such a great overview of not only the critical component of deep learning (shallow learning model, gradient descent) and technical details of how to achieve these models with python and numpy. I am so grateful for Dr. Ng for providing this wonderful lecture and am looking forward for further courses in this specialization.

Surprisingly Easily Understandable!

Andrew explained the machine learning concept and its equations intuitively. Programming exercises are hand holding but yet confirming understandings from lectures.

With basic calculus, linear algebra and python skills, you would pass this course easily with good understanding at the end.

Excellent course. I would have appreciated a stronger refresher on matrix calculus, perhaps with explicit examples. Nonetheless, I learned a lot! I'm excited to apply my skills in sheaf theoretic methods and algebraic topology to neural net architectures. I'm insanely curious about demystifying the "black box" so to speak.

It is nice that while considerable effort is made to avoid scaring people off with math, the content is not dumbed down as in some other courses. With a PhD in Math I still found the content quite engaging and new concepts were explained very clearly with intuition behind them. Looking forward to the rest of the sequence!

This is an amazing course which takes you step by step from the basics and builds all the foundations needed to understand forward propagation and back propagation passes which are key components of any NN. Slides are comprehensive. Along with that it provides you hands on exercises for implementing what you have learned.

I loved everything about this course. It is brief, repetitive enough for it to sink in properly, and the exercises are broken up into nice chunks.

The only addition I would have is to have some additional material or exercise (ungraded) for people who do know calculus, since the level required is only high-school calculus.

The course is designed very well. I felt that the learning curve is very good (not very steep or very plain). The course flows from quite detailed implimentations to a higher level implementation. The detailed as well as the big picture is visualized excellently. Thanks a lot for the efforts put up to prepare this course.

Great course! Thanks a lot, Andrew and team!

I liked very much how well-structured is the course material and how simply the theory of neural nets was explained. One of the best course I tried.

In order to make the course even better it would be great to add more programming assignments (more difficult), perhaps optional.

Andrew did a wonderful job on explaining the deep learning models. The programming assignments are very helpful to understand the models thoroughly. The interviews with legends in the deep learning field at the end of each week's course is an absolute pleasure to watch. Thanks for the team to offer us such a great course.

It was an excellent course. The course taught me a lot in understanding the foundations of deep learning. The assignments were very helpful. In my opinion, Prof.Dr. Andrew Ng has great teaching skills. I hope to continue with the next course in this specialization and I will definitely recommend this course to my friends.

Thank you Dr. Andrew Ng for explaining me in real sense what backprop is, some material I found was repetitive in Week 3 and Week 4 but in the end I got to know that was required. Awesume programming assignments. Thanks a lot! I feel that doing this course has made me more confident in basics that most people are lacking.

Awesome course! Had a great time taking this course.

The only bad side was the first interview in week 1. Although optional, I feltlike wasting 40 minutes of my precious time :) for not understanding any single word of a complicated discussion on deep learning topics I've never heard about.

The rest of the course was great.

This was a very thorough introduction to deep learning and it's application. Unlike the ML course which was in octave this was in python which made me love this more as it's very commonly used language and hopefully the skills learned will be transferrable. Would recommend this course to anyone interested in Deep Learning

The assignments are made in such a way that anyone with a basic understanding of neural networks can also solve. It is more of a spoon fed learning than assignment. I think it can be slightly changed to make the person giving the assignment use more of their gained knowledge than the hints (as comments) in the assignment.

I really enjoyed Prof Ng's course, his lectures are crystal clear and comprehensive, the assignments are thoughtfully designed to help you understand the theory completely and guide you step by step practically, I have learned a lot. I love these annotations in the assignments. Thanks for offering such an amazing course.

I gained a deeper understand on what constitutes a deep neural network. And also clear notations have been laid out to deepen the understanding and standardize the implementation of neural networks. Also it has been shown how to structure the code of the neural networks if you are starting the neural network from scratch.

I now know how deep learning works and it is all thanks to this course. I took a machine learning course but this showed the theory and application with deep learning. I have a physics background going into computer science and this course has definitely given me a skill in South Florida where most people don't have this!

Great course which provides a detailed mathematical and numerical overview with rigour and mathematical notations, and follows it up with focused exercises to implement neural networks and deep learning algorithms from scratch. Course covers practicum which I liked a great deal, and explains things crisply and succinctly.

Excellent course! As someone who has been out of college for over 24 years and hasn't had linear algebra and calculus for at least that amount of time, I would suggest that some some side material be added for a refresher course on both of those topics.

Kudos to Professor Ng and staff for putting together a fine course.