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.

I am thankful to Coursera for providing this costly course to me free and It was a great experience to learn new things and it helped me a lot. Thankyou Coursera.

Great instructor and just the right amount of challenge to keep it interesting. Would definitely recommend to anyone looking to get their toes into deep learning.

This course is wonderful. Really you don't need much mathematical background. Andrew teaches everything very nicely. The programming excercises are very detailed.

Andrew's course is always so intuitive and clear. I am so impressed at how the notebook is structured, as long as you spend time, you would never fail the course!

I really appreciate this opportunity to attend this course. I love the style of professor Andrew Ng very much. I will continue to learn more. Thank you very much!

You really need to have a background in linear algebra and analysis in order to fully enjoy the course. Otherwise, you are just applying formula without thinking.

The course enabled me to understand how neural networks work in a highly practical way. The concepts are explained very well and reinforced throughout the course.

Excellent refresher course for neural network. Suits better to the persons like me who already know some stuffs of Machine Learning. Assignments are easy but big.

This is an excellent course to learn neural networks from basics. Prof Andrew Ng nailed the concepts very well. The programming assignments gives a good practice.

This course is wonderful! But I think the coding assignment is too simple. More content should be assigned to students instead of being completed before we do it.

It was the best online course on machine learning. Loved the way it carries forward the knowledge transfer along with examples and assignments on real-world data.