编程作业感觉难度太低了，只要稍微听下课，然后代数学的还不错，就能通过注释将代码还原出来，虽然作业能拿满分，虽然原理理解的也还不错，但是只有自己亲手通过编程将理论知识实现实现一遍（非课程后编程练习，而是自己重新实现一遍，可参考课后练习），这样的感受才是最深的，即使这样，也并不能妨碍我认为吴恩达教授讲的非常不错。

Very nicely structured and presented. I really appreciated the fact that the exercises did not require any unusual python packages and could be run online.

This is a great course that teaches you the fundamentals of deep learning from scratch. Come with an empty mind and you will have an amazing journey ahead.

I would also like to know how these techniques are invented, like how they ended up using these models. Hopefully I might learn those in the later courses.

Very clair and the homework doesn't need you to have a pretty good level in maths. However if you want to learn it better, I'll still recommand some maths.

I applaud the effort and the teaching style of Dr. Andrew Ng and all the others who contributed in the whole materials. Thank you from the bottom my heart!

It was the great course i have ever done , (best for the deep Learning course ) ,

Thanks a lot for sir Andrew Ng , you are god of ML and Deep learning !!!!

Very good introduction into NN and DL with good programming exercises to get started

(requires some background knowledge it programming and linear algebra)

Fantastic way to learn in building complex neural networks. Step by step, teach us how to implement layers, activation functions, cost functions and so on.

本次Andrew为我们带来了更好的神经网络入门课程，相比于《机器学习》课程，该课程的编程作业和课后选择题的题量更大，且jupyter notebook的作业形式使得学生必须过目所有代码，这加深了学生对于神经网络的理解，且jupyter的交互式特性也使得学生能够更快地得到反馈，有利于更好地掌握python编程。

Really great course for learning essential concepts about neural nets. I only wish the homeworks were harder but they will surely teach you lots of things.

Very clear and good explained lecture, well designed assignment. It really make me understand when I build a deep learning model from scratch all by myself

Dr. Ng patiently and thoroughly explains the mathematics and code behind shallow and deep neural networks. A very well-organized course - highly recommend.

Incredibly well designed course! I took a lot away from taking it; I definitely recommend this course to people who are interested in deep learning at all.

I have learn basics of neural networks and its working. This specialization is really amazing everyone should take it for better insights of deep learning.

Good intuitive explanation of the basic building blocks of deeplearning. The Jupiter notebooks is a nice and useful way to implement python coding without.

This course is an excellent starting point. It brings out the motivation and operation of basic Neural Networks in an intuitive manner. Highly recommended.

Great course! Dr. Ng breaks things down very well and makes sure all the concepts are easily accessible and thoroughly explained for the student. Loved it!

Well explained, flexible on math requirements, exceptionally good exercises on programming - allow you to learn in depth the theory and put it to practice.

Great course! Well organized materials and super practical problems to work on as programming assignments which just make the learning process so much fun!

Dr. Ng is a great instructor and I'm so glad he launched this specialization. There is no one better than Andrew Ng to teach deep learning, he is the best!

This was a fantastic journey! I'll definitely follow Deep Learning specialization. The ability to see your results on some real datasets is just fantastic.

It was very clear introduction to Neural Networks. If you have a problem with understanding forward/backward propagation methods, so welcome to the course.

Very clear and easy to follow. ESPECIALLY for anyone who have been exposed to calculus and linear algebra, although he seems to describe everything needed.

Great. In one course you will be able to implement NNs with generic numbers of layers in Python. Andrew is great teacher, I cannot stop watching his videos