- All DegreesExplore Bachelorâ€™s & Masterâ€™s degrees
- Bachelorâ€™s DegreesExplore masterâ€™s degrees from leading universities
- Masterâ€™s DegreesExplore Computer Science & Engineering degrees
- Postgraduate StudiesDeepen your expertise with postgraduate learning
- MasterTrackâ„¢Earn credit towards a Masterâ€™s degree
- University CertificatesAdvance your career with graduate-level learning

Back to Neural Networks and Deep Learning

stars

117,857 ratings

In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning.
By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural networkâ€™s architecture; and apply deep learning to your own applications.
The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

RG

Sep 6, 2020

I have learned a lot from this detailed and well-structured course. Programing assignments were very sophisticatedly designed. It was challenging, fun, and most importantly it delivered what is aimed.

SM

Jun 13, 2021

Andrew Ng is one of the best teachers out there to learn NNs and DL. His deep insight into the math of the subject gives us motivation to learn more, amazing course to learn the basics of the subject.

Filter by:

By Mark D

â€¢Mar 22, 2018

I loved the programming assignments. The tasks are nice, the visualization of the neural networks' decision boundaries is very helpful, and the setup with the Jupyter notebooks is just awesome. In other courses it is often required to set up a programming environment first, which sometimes takes more time than the programming exercises themselves. In this course it was possible to dive into Python and Numpy immediately - without worrying about file paths, environment variables, compatibility issues and other nuisances. The lectures were also very good. All the concepts were explained very well.

By Rahul K

â€¢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! :)

By Omair M

â€¢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.

By Somnath M

â€¢May 17, 2020

I had always wanted, formulae on the research papers to make sense in real world applications. However, as a novice programmer I wasn't been able to put those formulas into code and had to always go through multiple links and videos to make it working which was really a bottleneck as I didn't knew where to start. This course is really comprehensive and well crafted to make one understand the very basics to build a Neural Network and use them any Deep Learning Requirements. If you have a intermediate Python understanding, than no other course can help you create your own Neural Net. Thank You!

By MANUEL A F C

â€¢Dec 31, 2019

El primer curso de la especializaciÃ³n no solo te presenta el aprendizaje profundo de forma teÃ³rica sino que se ve reforzada con los ejercicios elaborados en el lenguaje python. Terminando con una construcciÃ³n 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, asÃ como, practicar uno mismo implentando las funciones y decifrar que es lo que realiza cada lÃnea de cÃ³digo desde un inicio para no perderse despuÃ©s (recomendaciÃ³n: lean los foros). Excelente curso.

By Sahil M

â€¢Aug 20, 2018

Andrew sir introduces the idea of neural networks using a single neuron(logistic regression) and slowly adding complexityâ€Šâ€”â€Šmore 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.

By Ye W

â€¢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!

By GAUTHAM M N

â€¢Oct 6, 2020

It is a fantastic course for any one craving about the thrills of programming or math. Anyone without prior knowledge of programming can learn to like this course a lot. Knowing a bit basic math about matrices and calculus kinda makes it more fun, but no compulsorily needed. I am enrolled to all 5 courses in this specialization and will complete all of THEM! Andrew Ng is simply too good :)

P.s: It will get tricky a bit, because the 'what' of deep learning is tough to contemplate. Dont worry too much and just keep learning the 'how'. As time progresses you'll be able to understand it finally.

By Qiongxue S

â€¢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.

By Chris R

â€¢Sep 9, 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.

By Balwinder C K

â€¢Nov 9, 2020

Simply Awesome. I took another course from Andrew Ng (Machine Learning) 4-5 months back but didn't get much idea what's going on. Then i planned to take this deep learning course but before that i did quite to grasp the concepts. I must have watched the other course's video 50 times and must have done 50 small ML examples but that was beginning. This course was breeze as I knew this time the terminology, the concepts and specially what i wanted to learn from the course. It's always good to know underlying concepts as it give you power to debug the not so subtle scenarios.

Thank you Andrew

By Khizr M K

â€¢Apr 18, 2020

The course is very good and I found it really easy because I was familiar with python. There are two things which I want to suggest in your courses .

The first thing is you should also teach how to use python libraries for deep learning. This will teach students how to use library in different types of problems.

The second thing which I found was the course was bit easy and it should be made little bit difficult by removing certain hints such as formulae. This will force students to make notes seriously while listening your video lectures and implement formulae in their code on their own.

By vuhaluu

â€¢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!

By Karl-Andero M

â€¢Oct 4, 2020

I really liked the way the python exercises were structured (Jupiter notebook). To let the student only focus on course-specific code, and not implement the entire program from scratch. The only downside to everything I learnt is that I did not develop the intuition for the mathematical formulas of backpropagation. I tried and I watched the optional videos as well but it was quite difficult, because I haven't done calculus in a while. I will rewatch and try to understand that part better. Everything in the course was perfect, will be looking forward to learning the next ones. Thank you!

By Hugo P

â€¢Dec 6, 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!

By Sandeep M

â€¢Feb 17, 2022

Absolutely stunning course. Professor Andrew Ng really took the effort to tailor the course in such a way that complete newcomers to the field would be able to follow, imbibe and implement the material practically. The explanations on various topics are just amazing and the way advanced topics are introduced gradually on easy-to-understand basics was astonding. And by the time the learnings are implemented on the programming exercises, the concepts are driven hard and everything starts to make sense. I can't thank Professor Andrew Ng and Coursera enough for coming up with this course.

By Yasoda S K

â€¢May 23, 2020

I really enjoyed this course, as far as my knowledge is concerned no other Instructor make this course as understandable than Andrew. Being a person from different background initially I am scared about gaining intuition about the topics but Instructor explains everything in a lucid manner. I am very happy that all the programming assignments are guided in this course, a person with introductory knowledge in python can attempt and gain good grades. I recommend everyone who wants to take this course upon interest can take without hesitation irrespective of their area of study. Thank you

By George Z

â€¢May 19, 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.

By Ivo G

â€¢Jan 21, 2021

This course is very complete and takes plenty of time completely covering linear algebra, calculus and programming. If perhaps a bit slow this certainly helps whenever there is something you might not understand at first. I have found the high quality programming assignments to portray exemplary structure in the code and a very accessible way to get some experience working with different machine learning models. The course is setup in such a way that it can be comfortably done alone (haven't really tried the forum). I feel well prepared to get to work on my own deep learning project!

By HEF

â€¢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.

By Ronak V

â€¢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!

By Kemal A

â€¢Dec 7, 2020

I personally enjoyes this course very much. I think the videos are pretty straight-forward. I really like how every video offers a very brief, yet incredibly detailed recap of what was completed previously and what is about to be reviewed. I'd personally prefer more mathematics, but Andrew provides the equations and optional videos. This enabled me to derive all the equations manually and to compare my results with the ones provided from the course, whereas people less keen on maths were not bothered by this. I would recommend this course to anyone wanting to start neural networks.

By barryhf

â€¢Mar 27, 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.

By Stanislava F

â€¢Aug 31, 2020

Good balance between theory and practice. The best thing is that everything that you learn during the course you also try in the notebook, right away. So all the formulas and computations become very clear. I have been working with NNs for a couple of years by now and took this course to refresh the knowledge - and surprisingly I have found a couple of things I didn't know before (or have successfully forgotten about). I would also thank Andrew Ng for taking the interviews and sharing these inspiring videos with the students, it's very motivating hearing their stories and advice.

By Mohammad S Q

â€¢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.

- AWS Cloud A Practitioner's Guide
- Basics of Computer Programming with Python
- Beginners Python Programming in IT
- Developing Professional High Fidelity Designs and Prototypes
- Get Google CBRS-CPI Certified
- Introduction to MATLAB Programming
- Learn HTML and CSS for Building Modern Web Pages
- Learn the Basics of Agile with Atlassian JIRA
- Managing IT Infrastructure Services
- Mastering the Fundamentals of IT Support

- Basics of Computer Programming with Python
- Beginners Python Programming in IT
- Building a Modern Computer System from the Ground Up
- Getting Started with Google Cloud Fundamentals
- Introduction to Cryptography
- Introduction to Programming and Web Development
- Introduction to UX Design
- Learn HTML and CSS for Building Modern Web Pages
- Mastering the Fundamentals of IT Support
- Utilizing SLOs & SLIs to Measure Site Reliability

- Building an Agile and Value-Driven Product Backlog
- Foundations of Financial Markets & Behavioral Finance
- Getting Started with Construction Project Management
- Getting Started With Google Sheets
- Introduction to AI for Non-Technical People
- Learn the Basics of SEO and Improve Your Website's Rankings
- Mastering Business Writing
- Mastering the Art of Effective Public Speaking
- Social Media Content Creation & Management
- Understanding Financial Statements & Disclosures