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If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago.
In this course, you will learn the foundations of deep learning. When you finish this class, you will:
- Understand the major technology trends driving Deep Learning
- Be able to build, train and apply fully connected deep neural networks
- Know how to implement efficient (vectorized) neural networks
- Understand the key parameters in a neural network's architecture
This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions.
This is the first course of the Deep Learning Specialization....

Aug 27, 2017

This is a very good course for people who want to get started with neural networks. Andrew did a great job explaining the math behind the scenes. Assignments are well-designed too. Highly recommended.

Sep 02, 2019

I highly appreciated the interviews at the end of some weeks. I am currently trying to transition from a research background in Systems/Computational Biology to work professionally in deep learning :)

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von Sundar S

•Nov 27, 2017

Fantastic introduction to deep NNs starting from the shallow case of logistic regression and generalizing across multiple layers. The material is very well structured and Dr. Ng is an amazing teacher.

von Juan P

•Feb 12, 2018

I would love some pointers to additional references for each video. Also, the instructor keeps saying that the math behind backprop is hard. What about an optional video with that? Otherwise, awesome!

von Deven P

•May 14, 2019

This is really a very good introductory course for people from various background. The assignments are also nicely designed to give an insight to how things works.

But at times, in order to make this course appealing to non-math/engineering background, it at times trivializes some important mathematical concepts and notions, in order to not scare away people who are not very comfortable to mathematics.

von Antoine C

•Jun 04, 2018

If you are already used to Python/numpy and you followed the free Machine Learning course from Ng, you really won't learn anything, apart from a new activation function.

von Parth S

•Aug 10, 2018

Coding Exercise Were quite simple, a full length assignment would have been better.

von Ashkan A e A

•Nov 13, 2018

Too easy

von Zillur R

•Jan 04, 2020

At first, I want to thank the course teacher and all the others for providing us such a wonderful course. The way the professor teaches is really very very helpful. Thank you all again and keep it up.

von nikcojeanian

•Dec 02, 2017

Programming assignment is too simple

von Mohammad G H

•Oct 01, 2018

Very basic level

von Niloufar Y

•Jan 12, 2018

not satisfied

von Antonio C D

•Jan 19, 2019

A good mix of theory and practice. The learning curve was perfect for me, and the course schedule is right if you study the material and work through the assignments in your spare time. Assignments are very well structured, I feel that trying to create the same implementations by myself (i.e. without the guides in the assignments and intermediate tests / check) would have taken 10x long.

von Nikhil D K

•May 12, 2019

This is a good review of the concepts. It helped even more once I finished the course and reflected on the material by working out the equations for back propagation by my own hand. Looking forward to the next course in the series.

von Jerry P

•Feb 03, 2019

Excellent course. Challenging, but doable. Andrew Ng is a great teacher. I learned about logistic regression, forward and backward propagation, code vectorization with numpy, activation functions, and many other topics.

von Harsh T

•Jan 28, 2019

The course is good and it helps to clear the basic concepts of Neural Networks,

And the interactive assignments are just Awesome

von Juan A O G

•Aug 30, 2018

TL;DR: It's a good course for people who are not familiar with neural nets. Otherwise, it feels kind of repetitive (I completed the course in 4 days)

Pros: Learn to implement efficient feedforward neural networks from scratch, by taking advantage of vectorized operations and caches; good understanding of how neural nets work and the reasons of their success; I loved how Dr. Andrew explained why we must initialize the weights to some small random numbers (I already knew neural nets before this course)

Cons: I expected to build neural nets in Tensorflow (after learning how to implement them from scratch); It'd have been good to include a gradient check (by computing the numerical gradient) to foolproof the backward pass; sometimes the explanations felt kind of repetitive (e.g. continuously going from one training example to the whole training batch). I would have just sticked to the batch learning after it was introduced

von Jorge E C

•Oct 16, 2017

This course is good to just learn the terms and the basic aspects on architecture of deep learning. There is hardly any big explanations on the mathematical foundations of the topic which are of extreme importance to understand it.

It is a course for someone that dos not know much about neural networks or mathematics.

Is unfortunate that lead researcher in the area is able to say that it is not necesary to understand what a derivative is to be able to understand deep learning and the algorithm to update the weights of the network. I guess only for a first time course that is true, but I was expecting more from this course.

von Miriam G

•May 18, 2018

Really just mathematical background knowledge. Nothing you would ever need, since there is keras. No own thinking during assignments neccessary, either.

von Thomas M

•Jul 16, 2018

Course starts with a lot of math without any context what all those computations and parameters are used for or what they have to do with N

von Loren Y

•Feb 06, 2019

The assignments are not good. Too easy and too much handholding. Also lots of technical issues.

von Younes A

•Dec 07, 2017

Wouldn't recommend because of the very low quality of the assignments, but I don't regret taking them because the content is great. Seriously the quality of deeplearning.ai courses is the lowest I have ever seen! Glitches in videos, wrong assignments (both notebooks and MCQs), and no valuable discussions on the forums. Too bad Prof Ng couldn't get a competent team to curate his content for him. For such an basic level of content, you will find many other courses that are far better.

von Andrew H

•Apr 28, 2019

Not enough explanation or support to complete the very vaguely worded assignments in anything like the specified timescales.

I respect the source of this course but as a teaching resource it is really very poor.

von Ali A

•Aug 28, 2017

Terrible integration with Jupyter Python framework, end up losing 3 hours of work! Nobody responds from the courser team !

von Kenneth T

•Jun 05, 2019

Great course, definitely taught me the basics of Neural Networks and Deep Learning as it's supposed to. Assignments are quite engaging when you try to thoroughly solve them. Even with minimal mathematics, the course will handhold you the whole way. Definitely a great course for anyone with minimal programming to get into. For me, the most challenging part was understanding how Python syntax worked with numpy. If you are taking this course I recommend taking your time with implementing the projects, they can definitely give you an understanding behind the logic of neural networks by following the code. The instructor is quite nice and warm, sometimes a bit dry, but nonetheless, he seems very warm; wanting to teach the next generation of individuals to do ML/AI. The course does have a few downsides such as how buggy the iPython notebook can be. This is the programming environment you will be using. An the video quality isn't always the best with the audio, but overall the content was presented in a great way and prepared in a manner in which you learn one step at a time.

von William M

•Sep 04, 2017

I really enjoyed taking this course. I have taken one of Andrew's courses before, and they keep getting better. I have a background in development, and appreciated the use of python over octave. Andrew consistently strives to provide an intuitive feel for the topics he is presenting. The fact that he is able to provide a complex subject in a simple manner speaks to his mastery of the subject.

The course contained a great mix of theory and practical application of those theories. I'm looking forward to the next course.

von john g

•Mar 28, 2020

What an amazing course. To be fair, I had completed Dr. Ng's course "Machine Learning" before taking this particular course, so some of the concepts, I was already familiar with. This course, delved deeper into the mathematics of Neural Networks and followed it up with coding assignments in Python. This course has provided a strong foundation for me to continue to build my knowledge base. To anyone interested in Deep Learning, take this course!!!

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