It was a really interesting and easy course. Machine Learning/Data Science being called Electricity of the modern world have really made a mark in the start!

Lectures have been superbly planned. Time spent by key ideas conveyed is very optimal. Non-technical remarks were spot-on, added useful colour to the topics.

If you have no knowledge at all in AI and how things work, this is the best course to grab first. All you need is courage and a little bit of linear algebra.

Assignments could have been made more difficult and in depth coding sessions would be helpful. Also session on using plotting libraries in Python would help.

This is an awesome course! I would highly recommend it to anyone who's interested in DL. Andrew did very well in considering all the details for this course.

This course give me more confidence with deeplearning concepts and also help me to understand what is behind the forward and backward propagation algorithms.

Great introduction to neural networks. You need some basic math skills especially in calculus and linear algebra although it is possible to skip these parts.

Great Intro courser to get the intuition behind the workings of Neural Networks and Deep Learning. I am excited to do the next courses to see where I end up.

The course is a must for those who really want to understand how neural networks work. This is by far the best entry point for going deep with deep learning.

Very informative and well designed course. A must for all beginners or for someone who wants to go over the basics again. I like the programming assignments.

It extremely satisfies my needs. This course has taught me how a framework works and how we could develop a artificial neural network in Python by ourselves.

Remove the concerns of my ancient days of Calculus. A kinder-gentle approach to Calculus. Also the basics of implementation of Neural Nets/backpropagation.

I've dabbled in MOOCs before and this was the first one that I enjoyed from beginning to end. Great lectures, good lessons to reinforce the learning process.

Great course with implementation in Python which allows you to understand the structure of a deep learning network and how to use python for Machine Learning

Thanks Prof. Andrew for such an amazing course, learnt a lot. This course is must if you want to have strong foundation of deep learning and neural networks.

Great progression in the teaching, and great idea of providing a skeleton for the code an letting students fill-in the salient parts using Jupyter notebooks.

This course is perfect for a beginner like me who is familiar with some concepts of machine learning. The assignments are very interesting and fun to work .

Has provided a basic understanding of nueral networks and deep learning without diving much of the mathematical details. This course is perfect for amateurs.

这是一门很棒的深度学习课程，清楚的讲解了深度学习领域的数学原理，我跟随课程完成了一些练习，实现了利用神经网络识别一张图片里的图像是否是猫咪。在这门课程中，所有你遇到的难以理解的问题都能在后续章节里得到完美的解释与理解。非常感谢这门课程给我带来的提升与收获，我想这门课程推荐给了我的同学，他们正在学习，并且非常满意。

Andrew is a pretty good instructor to convey key points in quite clear expression. This course made me easy to understand why NN is a powerful model. Thanks.

Very good pace I really love it, I had some time that I couldn't study because of work but it gave me a couple of days to finish which make's it more awesome

Excellent short course on Neural Nets. Building 2 and L layer nets in a Python notebook using just NumPy helps develop a solid understanding of the material.

Wonderful course! Prof Ng has produced a great content and for people starting in the field, he has shown impressive example of implementing code modularity!

Great introduction to neural networks and deep learning. Covers all the key concepts and I found the interviews to be a very helpful supplement to add depth.

As usual it is difficult to get upset by Andrew Ng classes. I'd like a deeper math explanation even tough resources are offered . You will enjoy this course!