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 30, 2020

Amazing course, the lecturer breaks makes it very simple and quizzes, assignments were very helpful to ensure your understanding of the content. Hope for future learners you provide code model-answers

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 Eduard L

•Oct 31, 2018

After a full course of Machine Learning, of course, this one is rather weak. The feeling that all 4 weeks we are talking about the same thing. This is probably done for those who are not at all in the subject. I see this course as an introduction to the specialization. I hope the continuation will be stronger. It's great that practical work is done in Jupiter on Python. Program exercises are easy, but it takes a lot of time to figure them out if we don't know Python very well. This is not a plus or a minus, just a statement of fact. Thank you Andrew!

创建者 Bernard O

•Oct 21, 2018

This was an amazing course for me. I've always wanted to get to the bottom of deep learning fundamentals and this course did not disappoint. It walks me through the basics to the more deeper concepts in incremental steps without overwhelming me with too much derivatives (but just enough to carry the point across). Just the right mix of theory and practice. Highly recommended as a starting point for deep learning, or if you're like me, developing more intuition towards the practice that I am already doing. Fills in the gaps in my understanding nicely.

创建者 Steven K

•Jul 08, 2018

A very nice introduction to deep learning. Covers the basics and builds up slowly. There is some prerequisite knowledge of Python programming and calculus to have success with the course. Professor Ng's explanation of the topic is focused on practical applications, and builds on years of experience gained in academia and industry. The exercises are focused on mastering core concepts. The notation takes a little bit of time to get accustomed to, but you begin to understand why the notation is the way it is. Very good course; I definitely recommend it.

创建者 Romina

•Jan 08, 2018

A really good intuition and introduction to neural network and deep learning. What I enjoyed the most was the fact that we needed to implement the learning algorithm step by step through the guided programming assignments as opposed to calling an in built function in libraries ( such as tensorflow etc). I felt the programming exercises were quite very successful in an attempt to draw and maintain the learner focus on the algorithm itself as opposed to other programming aspects, which can be learnt elsewhere/improved elsewhere. Great course. Thank you

创建者 Juan

•Jun 27, 2020

I like the practical focus of this course, it allows you to build the fundamental parts of simple tools that are gratifying for us beginners.

The instructor focuses on making sure he teaches only the core concepts and sometimes he does only explain some concepts at a very surface level, but I see this as more of a feature than a bug. Linear algebra and calculus concepts that are only briefly discussed in this course, deserve their own class or course; I like that is up to the student to decide whether to deeply research these subjects on his/her own.

创建者 Ankur G

•Nov 13, 2017

This course makes you implement your own neural network without using Tensorflow or Torch. As a result, the student gets to learn what neural networks are implemented internally instead of only learning how to use a particular software package. The course is full of small, practical, and highly useful information such as why we use a cross-entropy loss instead of sum of squared errors loss and why do we need to initialize parameters using not-too-large random weights. This information is very useful in implementing NNs at work or for job interviews.

创建者 Wei L

•Aug 18, 2017

It's a very good course. It illustrates the idea of neural network and deep learning in an intuitive way. I think this time I fully understand the idea and details behind them. Also, the python programming is very friendly. I have used R for years but not so familiar with python. However, folloing the instructions I can do the coding very efficiently. I think i just spent less than 1 week on this course but get 100% score on it. So it's not so challening compared to Machine Learning and PGM. I think PGM is the most difficult one among these courses.

创建者 Dr. H K G

•May 24, 2020

Dear Prof. Andrew,

It is my pleasure to express gratitude and thankfulness to you and your team.

I am grateful to have you as a mentor in learning AI for everyone, neural networks and deep learning. It was a great journey with you in this learning process. Lectures and assignments made me realize the importance of the ANN and other advance tools in real world applications. The mathematical content behind neural network theory and programming assignments encouraged me to pursue this area in future.

Thank you once again.

Dr.Hari Krishna Gaddam, India

创建者 Nicholas K

•Nov 07, 2019

Overall, an excellent course! The material is taught very well. The programming assignments were enjoyable and fairly straightforward. The Jupyter programming notebooks were really cool and fun to work with.

The only criticism I have is that week 1 material was extremely easy, easily doable within a day. Week 2, on the other hand, was quite difficult. I think it was the most difficult week overall because it introduced a huge amount of new concepts and math. After I had a good understanding of week 2 material, the rest of the course was not so bad.

创建者 Rohan S

•Feb 24, 2019

This course is a masterpiece. Excellent for beginners and for those who want to refresh their memory. Andrew Ng's way of teaching neural networks with the simplicity of matrix multiplication deserves a standing ovation.

Course Content - 5/5; The material is extremely well structured.

Simplicity - 4/5; though the course requires basic calculus, it shouldn't be a problem

Assignments - 5/5; they were challenging, but it made sure that you grasp the concept completely.

Teaching - 5/5 - Excellent delivery by the master supplemented with easy explanations.

创建者 Christophe T

•Apr 07, 2018

[FR]

Excellent!

Très bonne introduction sur le Deep learning. L’instructeur nous explique les fonctions de base très clairement. C'est ensuite suivi d'une forme de TD ou l'on peut implémenter ces fonctions en python et s'en servir sur des cas concrets.

On ressort en ayant compris.

[ENG]

Excellent!

This is a very good introduction to deep learning. The instructor explains very clearly all the intuitions and the basic fonction of neural network. Then you'll have an assignement where you implement thoose function in python and use them on a real example.

创建者 Aditya V B

•May 05, 2020

A very beautiful course that introduces us to neural networks and helps gain insight on how neural networks work. One who doesn't know linear Algebra and/or Calculus can also understand the concepts. Programming assignments were good, helped visualize the neural network learning.

The derivations of gradients using Calculus should be proved/solved in an optional video, as it may help people with Calculus background understand the material in depth.

Overall, a very nice course to introduce Neural Networks and Deep Learning, would recommend 10/10.

创建者 Sarmad A

•Sep 26, 2018

Very well made. Andrew Ng taught all the core concepts of neural networks very well. Before taking this course, I've watched videos on workings of neural networks. Forward propagation and back propagation always seemed a bit hard to me but Andrew made these concepts very simplified and made me to understand them thoroughly. Extremely satisfied by this course, looking forward to course 2. I would recommend this course to anyone, no prior knowledge of machine learning is required. If you have any interest in this field, I would say just dive in.

创建者 harm l

•Aug 23, 2017

Great introduction in neural networks / deep learning. Using Python learning environment is easier than using R which causes me to spend lots of time in installing the right packages in the right versions. Drawback is that i don't have the programming environment ready after finishing this course. It leaves me with knowledge but i have to rebuild the models in a tool i can afford leaving me with lots of overhead things to learn and implement. Overall, good focus on the matter and it's a great surprise to have these results in such an easy way.

创建者 Thejus H R

•May 09, 2020

Andrew NG really knows his stuff, 10/10 would recommend in a heartbeat! Course is obviously complex, but well worth the time and energy you put into it.

If there is one suggestion that I could give, it is that the grading for the assignments be improved. The grader, in my experience, only gave me either full for each component or a zero. Any change I made in learning rate, etc, did not give me any partial marks.

Other than that, I cannot thank the team behind this, clearly a lot of work went into this seemingly labor of love! Thank you so much.

创建者 Ferenc F P

•Mar 08, 2018

Prof. Andrew Ng provides in this course a comprehensive step-by-step instruction to build up your own deep feed-forward neural network (DNN) with backpropagation using only the numpy (library for array manipulations). His approach is from bottom to top starting explaining very basic concepts as building blocks. After those bricks are ready you can easily build your own DNN. It is a great course for beginners wanting to understand how a DNN works. Notebook assignments are moderately hard for a beginner and easy for a programmer with practice.

创建者 Volodymyr B

•Jul 21, 2018

Great course! A lot of useful information; definitely worth it, even after taking the into course. I do have two problems:

1) I wish the programming assignments did not help you THAT much. The assignments pretty much tell you what to write. As a contrast, I think that the assignments in the intro course were much more challenging.

2) Although I was able to do the derivation myself, I wish there was optional videos to show the derivation of back-propagation, as I think it is a valuable piece of information for full comprehension of the process.

创建者 Milo C

•Sep 05, 2017

I have pass this class.

Except test case of L_model_backward is not match to the teacher, everything is very good.

For the learning strategy, I also have some suggestion for new learner.

If you don't has any experience about machine learning, then Machine Learning class in Coursera by Andrew Ng is good for basic background knowledge. It can help you to quickly understand in simple way. so you can quickly understand the course of Neural Networks and Deep Learning.

Thanks Andrew Ng make everything become simple and good to learn :) Thank you

创建者 BlueBird

•Jan 07, 2019

This Deep Learning course on coursera platform just meets my needs. The instructor of this course is Professor Andrew Ng, who has many years of experience in this field. His Instructional videos and textual materials can help me understand the essence of the theory of deep learning. In addition, after-class quizzes and programming assignments can also greatly increase our practical skills. Therefore I believe this Deep Learning course can help me to possess the basic ability to work in the field of artificial intelligence and deep learning.

创建者 Ryan S

•Dec 04, 2017

Very basic concepts are taught, but the material is presented clearly and relatively concisely. The concepts are very accessible and some depth on the mathematics and theory is provided, although not as much as you would get in a graduate level college class. The programming assignments are very good, balancing first-principles implementation with a focus on implementing the most important concepts rather than writing boiler-plate code. This is a good introduction for practitioners and is easily covered in much less time than that allotted.

创建者 Aman R

•Mar 18, 2018

Started this course 3 months back, but from past two weeks I sat for around 4 hours per day, to complete this course. The programming assignments may not seem difficult intitally, because Andrew provide the vectorised equations but what really boils down and deepens my understanding was how am I going to use it in my application. How I will build my own image classifier ? When I try to answer such questions then yes it was very very helpful to me. I am still in learning phase, a beginner, so yes course was difficult but it was manageable.

创建者 Jairo J P H

•Feb 01, 2020

El curso es muy bueno, particularmente estoy muy agradecido con COURSERA, por darme la oportunidad de hacer los cinco cursos de la Especialización en Deep Learning con ayuda economica y permitirme tener acceso a este tipo de capacitacion y certificacion. Muchas Gracias…!

The course is very good, particularly I am very grateful to COURSERA, for giving me the opportunity to do the five courses of the Deep Learning Specialization with financial aid and allowing me to have access to this type of training and certification. Thank you very much!

创建者 ayush k

•Apr 20, 2020

Course if fantastic starters, taking a mathematical approach to the design of NN. Assignments and quizzes are good as well.

However, The format of downloadable course materials need to be improved. It would be nice to see all the documents in one file for a certain Week, instead of downloading files separately. Basically the download format of ML course was much consistent and good for quick referencing.

But nonetheless, 5 stars because above is just my personal preference which has nothing compared to quality and content of the course.

创建者 SanjaySuman S G

•Jun 22, 2020

This is truly the best course for those who want to start learning Deep Learning. Our Instructor Andrew Ng , he is amazing!!! . The way he teaches all the concepts are really good , the programming exercises were really helpful.This is a well structured course right from logistic regression to implementing Deep Neural Network.

Overall I really enjoyed learning this course and will continue learning this specialization and apply my knowledge to real world problems. A big thank you to my Instructor Andrew Ng and Thank you Coursera team .

创建者 Sayed A B

•Jan 20, 2020

I've been interested in learning NN and ML for a long time and Coursera finally provided this opportunity for me to do it in a timely manner. The time was very limited for such a wide topic, however, I believe they deserve a 5-star for how they managed to benefit such a limited time in a very efficient way. Andrew Ng is one of the best teachers I've had. He's both very knowledgeable, explains the concepts in a simple language, and he's very humble at the same time! Looking forward to getting more courses with him and with Coursera ...