There are a lot of courses, books and other resources to learn but only this one provides enough and theoretical and practical information. The math explanation is simple enough to be understood by anyone. The assignments are divided into intuitive small steps which allows to implement complicated models.

the best thing about this course is the programming assignments. They not only helps in understanding the concepts covered in the lecture, but also provides confidence to implement things from the scratch in your own working environment. Further, the interviews with Hinton, Arbeel, Goodfellow are awesome.

This course shows the "bricks" of the neural networks and gives a good intuition of how they work. I also liked that you have to make a few neural networks from scratch, rather than use a framework or something like that. This course is a great start in the field. Looking forward to complete the next one!

I really liked the introductory course to the deep learning . I swear I have seen the changes in myself and all the credit goes to the coursera team . There is no course like this . If somebody says he has worked on the deep learning projects wonderfully either he is lying or he has seen these courses

I have really enjoyed doing this course. In fact I used to use high level libraries to build my neural networks, without a clear understanding of what is really going on inside the box. Now I am able to code my neural network from scratch and I now understand what is happening in each neuron of my model.

Many a times, when going through an Online course I don't get what's happening what. But this course had the right theoretical knowledge and concise walkthrough about everything. Along with it, the "intuition" videos really help getting a grip on the subject matter, and its easier to picture every step.

There is no doubt that Mr. NG is one of the best instructors n this area. His explanations are very clear and straight to the point. I am really amazed at his understanding and the way of teaching. The programming problems were also very much helpful. I am surely going to recommend to others this course.

I find this course as an excellent introduction to supervised learning.

The programming assignments where made in such a manner to encourage even those that are less familiar with Python programming. Even so the explanations and support helped a lot to get an idea of what's behind a simple neural network.

I love the teaching style through this course. The way the professor teaches make all the theory easy to understand and to follow. The assignments provides detailed guidelines to the coding instruction. Basically, it contains the pseudo code already and all you need to do is to transfer them into coding.

In my opinion, this course is pretty good.The content of this course be designed as a simple methods to learn and the homework was designed by your team ,it is very useful for me to understand this course and the progress of forward and backward propagation of deep learning .

Thank you Andrew and others .

As always, Andrew Ng' s course has high quality training material and he's really good at explaining the topics in a relatively simple way. Easy to follow and understand. Programming assignments are well designed, also some comments should be a bit more clear. Overall, worthy of the time you spent here.

Great - it took me until after the course to realize I could look the syntax up in external numpy documentation. Otherwise it was informative, if hard to guess at the syntax. Not sure if I can take one of their models and generalize it for my own use. That seems to require a different environment or IDE.

Understood the forward and back-propagation and why it is important to pick the right activation function for hidden layers as well as the last layer. I liked pretty much everything about this course. Details like how the A, Z, W matrixes shapes must look like were the things I came for in this course.

This course is well structured for getting started in deep learning and neural networks. There are graded assignments at the end of every week which help to implement the knowledge gained throughout the week. Even beginners with a little know-how of python and algebra can follow the instructions easily!

One of the best ever course on fundamentals of Deep Learning.

I had previously worked on lot of deep learning projects but lacked mathematical perspective behind it. Now everything is crystal clear giving even better intuition when working on projects.

Thank you Andrew, deeplearning.ai and Coursera team.

The perfect course to understand the principle and understand the practical implementation of Neural networks. In my opinion, taking part in the course "Machine Learning (Stanford University)" taught by Prof.Andrew NG made it easier for me to understand the NN concepts taught in this course much easier.

The course was great in introducing machine learning and deep learning. I have learned alot of concepts and coding techniques. However, I think it would be much better if the homeworks are alittle bit harder. At least one or few functions should be left for the students to write completely from scratch.

Ideal as first approach to neural networks. After completing this course, you really understand how a deep neural network works, even if you knew almost nothing about this subject at the start. Very good also from technical point of view and very well taught. Videos and Python notebooks are very clear.

Great course. Though i would suggest that one does in addition to a theoretical course. Prof Andrew was spot on as always. His CS 229 on stanford engineering everywhere is a remarkable supplement to this though it is much tougher than this.

I wish the programming exercises were designed in a better way.

Great introduction on the 'inner' workings of neural nets. Clear presentation on forward and backward propagation. Anybody thinking to make the step from 'classical' machine learning to neural networks and deep learning will not be disappointed by the lectures and the accompanying programming exercises.

It is magnificently explained. In this course, complex theory as the backpropagation algorithm is explained in a way that it is not difficult to fully understand what's behind it.

Also, tests and exercises are good to learn tips and advices for the time i'll be needing to implement my own neural network.

A great lecture from Andrew! The video, programming exercises and the course discussion forums are extremely helpful. Highly recommended for anyone would like to understand NN and Deep Learning - no previous experience required although some basic calculus and linear algebra knowledge will become handy.

Very good and enjoyable introduction to neural networks. Andrew gives an intuitive introduction to the key concepts in a clear and concise way. He doesn't focus too much on the underlying maths but gives enough details for anyone to dig deeper into the proofs or mechanics if desired. Highly recommended.

great course ! I like how Andrew Ng shows back propagation and how the cache is used from the forward prop. I truly believe I am learning a lot "deeper" framework than in the Udacity courses. I don't even think I'm going to do Udacity now because the learning here is so much clearer and straightforward.

Best Foundation to Deep Learning ever! You'll be amazed by your transition through the four weeks. Andrew Ng has got this knack of breaking down huge concepts and feeding them in, when you're unsuspecting! Special Mention - Heroes section: Pursue with your intuition even when nobody else believes in it!