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....

Apr 07, 2019

A bit easy (python wise) but maybe that's just a reflection of personal experience / practice. The contest is easy to digest (week to week) and the intuitions are well thought of in their explanation.

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.

筛选依据：

创建者 Rahul K

•Feb 27, 2018

Beautifully structured course! Feels like a walk in the park if you've already completed the 'Holy Bible of ML', i.e., Andrew Ng's Machine Learning course on Coursera.

Very good programming guidelines, and a gentle introduction to anyone who isn't aware of the core concepts on Machine learning.

If you're wondering whether you should complete the Machine Learning course first, by all means, go ahead. However, I can guarantee that there will be no hardships faced even if you're a beginner in ML and want to dive head-first into Deep Learning.

After all, it's Andrew Ng who we're talking about here! :)

创建者 Omair M

•Nov 25, 2017

Prof. Andrew Ng explains all concepts from a very fundamental level and even nervous students will feel encouraged by his insistence on "don't worry about it" for derivations you don't understand. The assignments have a lot of hand-holding but I needed that to focus on other more important concepts instead of debugging python code which can be learned in a different course. Overall, I have learned how to build a deep neural network using a building-block approach and gained confidence regarding this domain which I had previously taken to be mysterious and cryptic and perhaps for the elite only.

创建者 Manuel A F C

•Jan 01, 2020

El primer curso de la especialización no solo te presenta el aprendizaje profundo de forma teórica sino que se ve reforzada con los ejercicios elaborados en el lenguaje python. Terminando con una construcción guiada de una red neuronal de 4 capas y entendiendo cada paso pues son planteados adecuadamente en funciones definidas con anterioridad. Recomiendo ver cada video a detalle y tomar apuntes, así como, practicar uno mismo implentando las funciones y decifrar que es lo que realiza cada línea de código desde un inicio para no perderse después (recomendación: lean los foros). Excelente curso.

创建者 sahil m

•Aug 20, 2018

Andrew sir introduces the idea of neural networks using a single neuron(logistic regression) and slowly adding complexity — more neurons and layers. By the end of the 4 weeks(course 1), we are introduced to all the core ideas required to build a dense neural network such as cost/loss functions, learning iteratively using gradient descent and vectorized parallel python(numpy) implementations.

Andrew patiently explains the requisite math and programming concepts in a carefully planned order and a well regulated pace suitable for learners who could be rusty in math/coding. I love this course.

创建者 Ye W

•Oct 28, 2017

This course serves as a great intro. I saw many comments complaining that the course is a bit too easy. As a stats PhD student, I admit that the technical details in this initial course is trivial, but I feel that I learned a lot of useful things, e.g., vectorization, intuition, etc. In fact, the entire concept of deep neural net is very straightforward, i.e., nothing but a generalized linear model (GLM) from a statistical prospective. I feel what is important is the intuition behind it and how to implement it efficiently in practice. This course covers both aspects in great details, love it!

创建者 Qiongxue S

•Dec 14, 2018

This course helps me to understand what is neural network and how would we use the NN and deep learning method to solve the practical problem. This is real science. For the content I have to say that this is the best AI course I have ever had. The related theory and mathematic equations are all clearly explained. Besides I learned a lot from every assignment. The point to build NN is make sure we understand the theory first then the programming part will not be hard. But before learning the course I think we need to have basic knowledge about python. Excellent course! Thank you so much.

创建者 Chris R

•Sep 09, 2017

I have already completed Andrew Ng's Stanfor Machine Learning course on Coursera, but the neural network coverage was limited. This course helped me understand the underlying principles of deep learning more completely and I'll be taking all five to earn the specialization. The pace of this course seemed perfect for me having some knowledge of Python, linear algebra, and calculus. This course also helped to refresh older memories and learn new things about Python libraries like numpy. This is an excellent course and has left me very excited about possible applications for deep learning.

创建者 vuhaluu

•Aug 20, 2017

I took the ML matlab version that Prof Ng created, but could not make it because I could not understand the homework problems and the content of the course. Thus, I got out after the fifth week because I could not understand how to do the assignment. However, luckily, right after I got out, he opened this course. It was a relief that I was able to understand everything I did not understand from the previous one, and I was able to do the homework. Therefore, I would suggest this course to everyone who wants to learn AI. Thank you Prof Ng and your dedicated team for this tremendous effort!

创建者 Hugo M S P

•Dec 06, 2017

I loved this course and I got much more inspired to pursuit my search in this area hoping that one day I can join this amazing community and get a job in this area!

Thank you very much for your great work: loved the good sequencing of the videos, with very simple and bright intuitions about the more complex math topics, and also enjoyed a lot the Interviews with the gurus/legends of AI and ML!

Congratulations to all that participated and made such a great effort to put up this course available in such a professional format and by such a filantropic price!

Keep on with this outstanding job!

创建者 George Z

•May 20, 2019

The Neural Networks and Deep Learning class from Andrew Ng, deeplearning.ai and Coursera is very well structured and taught. I learned a lot and I am glad I was able to use calculus and Python to better understand what is going on underneath the hood with forward propagation, cost, parameters, backward propagation, predictions and more. Andrew and his team are exceptional instructors. The Deep Learning hero sessions are very motivational and inspiring. I also enjoy Andrew's sessions from Stanford's CS230 online. Looking forward to my next adventure in this Deep Learning Specialization.

创建者 HEF

•Mar 24, 2019

Before taking this course I have learned Machine Learning, which is another famous course in Coursera, also taught by Professor Ng. My feeling is that this course is not as intensive as that one, but still I learned so many new stuffs which are extremely useful in my own deep learning projects. Before taking this course, I had zero coding experience in Python and so was really nervous about the programming exercises. However, the exercises are very well organized that I think every one can handle easily. So what I want to say is, don't say you can't do it if you never give it a try.

创建者 Ronak V

•Oct 15, 2017

Not sure how other people would fare, but I felt like in order to have a deep understanding of what was actually going on, I needed to go study the calculus and linear algebra behind the material (which I had done previously). I know that probably turns a lot of people off and is why it's somewhat glossed over, but thought I'd just put it out there.

I will say that this course was super helpful with seeing how a theoretical understanding of DL translates into code. The coding exercises were 100/100. So thank you for that! :). Looking forward to the next courses in the specialization!

创建者 barryhf

•Mar 28, 2019

It's an honor to be taught by Professor Ng. He's an excellent instructor, and he has very effectively brought this complex material to those of us who are practitioners rather than applied mathematicians.

Perhaps if, like me, you are familiar with the mathematics used in this work, you might find the pace a bit slow. The repetition, and the guided programming exercises, do serve a valuable purpose. By the end, by the final exercise, there is crisp clarity on what all of the components of the neural network are, and how they are utilized.

Thank you, professor, for an excellent course.

创建者 Mohammad S Q

•Feb 19, 2019

First of all the course is designed and taught by AI pioneer Andrew Ng, the fact itself creates no room for any reason for not opting for this course if somebody wants to learn about DL.

Secondly, the approach is ground up, you get a confidence that without knowing or learning complex numerical foundations, you can get intuition of how deep learning works and can very well start applying this into your projects. When you see working model of a deep neural network built from fundamental codes, you feel like doing something and it makes you try harder and wider problems on your own.

创建者 Naima

•Sep 27, 2017

The course is very helpful. Andrew Ng has explained all the basics of neural networks. Both theory and programming lessons are very neatly arranged. It helps freshers to learn a lot. Since in programming assignment, the theory and notations needed for that are also explained I could connect everything fast. And I didn't had to code everything in python. It helps people who are not that much expert in python and its an inspiration to learn more in python and other technologies. I express my gratitude towards Coursera and Mr.Andrew Ng for helping for this course. Thanks, Naima Vahab

创建者 Christen

•Sep 09, 2017

I had almost zero knowledge about Python language and even less about all the complexity of the internal structure of neural networks (NN). I can imagine how difficult is teaching this sort of witchery to common mortals but Andrew Ng. did a great job on that simplifying and remarking just the practical and important points you require to build a simple NN. It's a clever way to start in the world of deep learning despite of the high price of this course, otherwise it could take ages learning by yourself. I wonder if I will become a kind of wizard when I finish all the 5 courses...

创建者 Sabarish V

•Dec 03, 2018

The course takes a very direct approach to building your first neural network. It has very little maths, and the coding is extremely simplified in the assignments. For someone with a little bit of background, it wouldn't take more than a couple hours to be done with the course and running your first multi-layer model. If you have prior knowledge of NNs, machine learning, or calculus and vectorization, the course could feel a bit tedious. In this case, I'd recommend running the videos at 1.5x or 2x speed .

My only gripe is the quality of the audio. It could have been much better.

创建者 Eche I

•Oct 12, 2018

I was initially running from the maths that underpins deep learning but this course made it some much easy to understand and gain intuition on how to operate deep learning. I thoroughly enjoyed Andrew's style of delivery and with his constant reassurance and I quote, "don't worry about it …", that holds very true and gradually makes you fall and gets the underlying linear algebra, calculus and derivatives that form the theoretical backbone of deep learning. The course really left me on the high and with a strong grounding to begin to press further in this deep learning journey.

创建者 Assaf B

•Aug 22, 2018

If you had Prof Ng's "Machine learning" in the past, you expect perfection, so you may say that this course had imperfections such as Jupyter work instead of offline work, which confines your creativity when working on an exercise, and the course bit short, even for a chapter in a specialization.

However, when comparing to other courses, to nearly any other MOOC except "Machine learning" and perhaps "Complex Analysis", this course is still a DEFINITE five stars course. In content, in knowledge bang for your time invested, in usefulness, in teaching ability, and the list goes on.

创建者 Karim W E A

•Aug 15, 2017

A lot of repeated material from Stanford's Introduction to Machine Learning, especially week 4. But of course, implementing all the assignments in Python, which is probably the most widely used language for ML and one of the most efficient ones as well; That was a big advantage over the material covered in Introduction to Machine Learning. Also, the material was explained in great detail and was tremendously organized. Would highly recommend the course to anyone who's looking into expanding their knowledge in Deep Learning. I can't wait to start Course 2 in the specialization!

创建者 Ricardo S

•Nov 24, 2017

I found this course to be a good introduction to neural networks and deep learning geared toward the uninitiated. For anyone with some experience however, the course can be rather easy, though it can serve as a review and it is fast enough to go through. I find it to be always good to start from basics, especially in the complex and always evolving field of machine learning, and this is an adequate starting point. I suggest that anyone taking this course with serious aims should seek to understand the mathematics introduced in it, though it is often mentioned as "not needed".

创建者 Mark M

•Jun 20, 2019

The programming assignments in this course provide practical experience in building a deep learning neural network. The lectures are thorough and easy to understand, and they connect clearly to the quizzes and assignments. I'm grateful that Professor Ng and staff put this excellent resource together and make it accessible to all. I currently work in Cambodia, where I hope to introduce courses such as this to young people who have no educational opportunities. I highly recommend this course to all who wish to be aware of the incremental significance of AI in our time. Thanks!

创建者 Aayush K S

•Apr 06, 2019

Really great course material. With minimal mathematics behind this, this course provided a great start to deep dive into deep learning. The video length and the quizzes and exercises were great. Also, since jupyter notebook was hosted by coursera itself, I didn't had to invest setting up infrastructure or downloading packages in my local system which was unlike AndrewNg's MachineLearning course which used Octave. This experience made completing the exercises more efficiently. helping me to utilize most of my time in solving it. Looking forward to complete the next courses.

创建者 Matteo C

•Mar 08, 2018

A great course.

The topic is very compelling on its own, but the magic is all in the instructor. Andrew Ng is passionate and explains complex concepts by slowly building up to them. It was very important for me that he introduced the math and notation required, without assuming a lot of prior knowledge.

The programming assignments are worked on and submitted with Jupiter notebooks, which is great.

To make the most of this course, I would recommend doing the "Machine Learning" course from Andrew Ng, as it has a lot of relevant content and a good refresher on linear algebra.

创建者 Casey K

•Mar 08, 2018

Definitely recommended. I've taken various other deep-learning lessons and tutorials, but none of them gave me as much insight and practice as this course. I get the feeling that a lot of work went into the design of the course and even the homework problems.

A practical note for people considering the class: it'd be a good idea to review how matrix multiplication works before diving in, because that comes up again and again. There's a review in the course itself, but it doesn't come until week 4, and I found it necessary to analyze matrix dimensions as early as week 2.