I went from having a good theoretical intuition about how deep networks should work to direct knowledge about how to implement one. Amazing class, thank you!! :)

A great introduction to deep learning, I would have liked more mathematics involved, but I understand why it was necessary to cut back on math. Highly recommended!

Phenomenal course by Professor Andrew Ng. The concepts are throughly explained and the assignments are extremely engaging.

Thanks for offering this specialization!

I would like to thanks Andrew and all people involved in this course for all the effort they put in this course. I have learned a lot and had great time as well.

The explanation builds up over time, that's what I love about this course. I was frightened of this very topic, because other courses didn't explain it like this.

This is an excellent course. Thanks to Andrew NG sir for providing us a beautiful content. I learned a lot, and I will learn a lot more in this domain. Thank you.

This course addressed all the issues that Machine Learning course had. This course is easier, more interactive and had a much more consistent learning experience.

Clear and well structured. One observation: a reminder on matrix calculus, the same kind that the one on derivatives, would be nice before heading into equations.

This course gives me good understanding about the math logic behind the code. It will help when designing new algorithm, Mainly while troubleshooting an Algorithm

Thanks to the Coursera team for providing such a nice environment to learn easily, though I don't have a good GPU the online lab activity is really appreciatable.

Very interesting course, I really appreciate how much assistance is provided in the programming assignments themselves because I struggle a lot with writing code.

This course is a really good introduction to neural networks and I have to say that programming assessment are very exciting and motivates me to continue learning

I am not new to deep learning. I have done it without knowing the inner details well. I felt confused what to do if my model failed. This course is an eye opener.

Wonderful course. Thanks to all Coursera team and deeplearning.ai staff. Very grateful of your well done job and for giving this opportunity to worldwide students

Very comprehensive and informative introduction to deep learning. Everything is step-by-step and clear, from the math to the explanations and the coding examples.

It is an amazing experience to be able to follow Andrew to get a comprehensive understanding on deep nn network and implement the fp and bp yourself with python.

Очень качественный вводный курс. Даже человек без математической подготовки сможет его пройти и понять основы построения нейронных сетей. Спасибо авторам за курс!

This course has great content and i prefer every cs engineer if they are looking for neural network and deep learning course ,the this is the best course for it .

I loved this course, the math background is perfect to truly understand what is going on behind those simple lines of code used to train and test neural networks.

Very nice course! Comprehensible and didactically well structured. I really enjoyed watching the videos and passing the assignments as a nice after-work activity!

Вирішив бути оригінальним і написати "рідною": Чудовий курс. Усім рекомендую - викладення доволі легке, англійська зрозуміла - що ще потрібно для занурення в МН ?

Explains the basic concepts of Deep Learning and the use of Matrices within it very well. Concept of Forward Propagation, Backpropagation and Cost are made clear.

All the basic concepts have been explained in very simple way.

Thank you for making such a great course. Assignments are very important to strengthen the learning.

Very well done class. It was a great way to get started in deep learning. This class does a good job of introducing neural networks and the intuition behind them.

The videos and programming exercises are both delivered in super clear logic, which makes them incredibly easy to follow and has been keeping me really motivated.