Back to Neural Networks and Deep Learning

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20,941 reviews

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 network’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....

OO

Oct 20, 2017

Andrew Ng's presenting style is excellent. Makes the course easy to follow as it gradually moves from the basics to more advanced topics, building gradually. Very good starter course on deep learning.

AA

Sep 1, 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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By Pulkit B

•Oct 14, 2020

Great course to get hands on into implementation of neural network. It forces you to learn everything from scratch. Also I liked the notation used, and the clarity with which Andrew Ng explains the concepts.

Just one thing though, if the coding assignments had given much more work to us to figure out and do ourselves that would've been much more challenging. I felt that often the instructions given just before the exercise were pretty much a giveaway in terms of what code needs to be written.

By Jay A

•Apr 20, 2020

Excellent intro course to deep learning. Andrew does a good job of taking students through the basics all the way to the development of a deep neural network. I particularly liked his depiction and explanation of the forward prop, back prop process through the graph. The assignments are challenging and superbly structured such that with some thought and effort you can succeed and actually implement the whole network. I would highly recommend this course to anyone curious about deep learning.

By Hrushikesh V

•Jun 11, 2020

The course is pretty thorough with the theory as well as with the practicals. However, I did feel that I would have understood the implementation procedure much better if there was one more programming assignment per week. Regardless, I was able to follow the course and I'm excited to take the next course in the specialization. I feel like you would be able to follow this course much much easier if you have a good amount of experience with Python and at least a basic understanding of numpy.

By Juan R C C

•Sep 14, 2017

After complete the Machine Learning Course, this one has been more easy to complete than it and, thanks to Python programming, easy to align with other related courses where there are programming assignments.

In addition, it's a pleasure to follow trainings delivered by Andre Ng. His teaching quality is outstanding.

The only "but" is that I missed to use DNN with multiple classification and not only binary classification. Probably it will be covered in next courses into the specialization.

By Maciej B

•Aug 19, 2017

Course is nicely constructed. If you have 2-3 days without other commitments (I didn't) you can finish it very fast including all the - non-required - computations on paper. Coding excersises are well designed although not very demanding. Additional, more complex (bonus) excercises would for a nice add-on to the main course.

The only problem I have with the course is that I must wait 4 weeks for the next step, despite finishing the first stage during the first week. I do not understand why.

By Fernando D G

•Mar 4, 2018

I can not express the amazing professor Andrew is. He is capable to explain complex concepts in a way anyone could understand.

I would also like to say that the assignments of this course are amazing. They have taken a lot of time to create the Python notebooks and to match every single line of code with what was showed in the lectures. It's almost impossible not to get confident with Neural Networks after you have completed all of them.

My sincere congratulations to all the teaching staff.

By Joyce G

•Jan 21, 2018

Absolutely wonderful! I have strong math and CS background. I can see this course can be learned by many people from many background.

VERY helpful. I cannot say enough good things about it! Thank you so much!!

The only one thing is that it will be great if the homework assignment deadline can be even more flexible. I work full time and I have a big family. I have been working holidays and weekends to get the course done. It will be nice if the deadlines are more flexible for people like us.

By Nilesh I

•Oct 29, 2017

Awesome course. The teaching style of writing down each small step made it easier for me to understand complicated concepts. Previously I had taken the ML course. Here, the course starts with a simple logistic regression as neural network then 2 layer NN and multiple layer NN. The assignment projects have clear explanation to guide through the assignment projects. The forums are a great help to find cause for errors etc. Thank you Prof. Ng. Looking forward to other courses in this series.

By Devansh K

•Jul 1, 2020

Excellent course! Concepts were explained very clearly and concisely. I really appreciated how much detail the instructor went into. A lot of courses and resources tend to brush over important concepts and just focus on practical applications. It helped a lot to learn the nitty-gritty details that make neural networks work. The assignments were reasonably easy and informative. Only possible improvement for me would be to have more detailed explanations of the calculus behind the networks.

By Pooya D

•Mar 24, 2018

A great introduction to machine learning using neural networks. This course provides a general overview of the mechanism of prediction and optimization of the prediction (gradient decent) using a neural network. The hands-on approach and the minimal lecture videos makes the course interesting.

(I think there might be a way to revolutionize the concept of Discussion Forums to make the learning more interactive with fellow learners but I don't know how so I don't blame the course creators!)

By Ravi R

•Sep 21, 2020

It's a very good course for beginers in machine learning. Every theoritical aspect of Neural network was explained brilliantly by instructor. Andrew is perfect in his job. But i was little bit disappointed in programming exercises because i don't know much about Python so i didn't understand some of its functions and mainly its imported libraries of Jupyter notebook. There should be one more class or at least a document to explain the libraries and function used in programming exercises.

By Ashwini J

•Dec 18, 2019

Neural Networks and Deep Learning course has been a great learning experience, I had high level idea about how a Neural Network works, having used on structured data before through packages and libraries. But after completing this course and building a neural network from scratch using only numpy library, I now have a good understanding and intuition about why a neural network works. Kudos to Andrew Ng and his team for putting together the content and assignments. This course is helpful.

By Michael F

•Aug 29, 2017

Another excellent course by Andrew Ng. His instruction style is detailed, without getting into the weeds. The lectures provide enough background so that people with (like me) and without detailed linear algebra backgrounds can understand how these algorithms work. There is also plenty of resources available for helping with programming and other details of implementing these strategies. Highly recommended if you want to learn more about neural networks and how to actually implement them.

By SAJAL S

•Aug 22, 2020

This is a great course for AI and ML enthusiasts to start learning and making deep learning models. The explanation technique is really good, which makes learning it even more interesting and involved. The programming assignments are intuitive and involving. All in all, if you want to start out in Deep Learning, this is the place for you.

It doesn't matter if you don't know or want to learn the complicated mathematics involved in this field, because Andrew Ng has you covered for that :D

By Mihai L

•Jan 7, 2018

This is another excellent course from Andrew Ng.

After doing his Coursera Octave based initial Machine Learning course I thought I might get up to date to Python /Numpy techniques.

As usual it was excellent. Assignments were not too difficult and you can resubmit multiple times (both quizzes and programming assignments).

Being able to use iPython Notebooks is a great positive point. Installing Python3 + Tensorflow with GPU support took me a long while (just before starting the course).

By Eunis N

•Oct 15, 2020

This course breaks down deep learning concepts into small enough to digest pieces. It's a very well-structured course and it takes away the fear of calculus and matric calculations. What I liked the most about this course, besides Prof. Andrew Ng, is it gives explanation for the correct answers to practice questions, which not all the courses do. The assignments are very well put together with lots of self-help remarks. I recommend this course to everyone, even the non-mathy learners.

By Bilal K

•Feb 25, 2018

Andrew Ng is an amazing instructor! This is the best explanation of deep learning and neural networks that I have come across. I love how he explains everything from the basics and still covers so much ground. I was intimidated by backward propagation before taking this course. But after going through this course, it seems it is just a fancy name for the chain rule I learned in high school calculus.

Andrew's dedication to helping others learn shows in every lecture. He is a rock star!

By Ram

•Feb 5, 2018

Very complex concepts have been taught without assuming much mathematical background. Andrew is an extraordinary teacher. I aspire to become as good a teacher as him one day. Also the programming assignments are well designed. The Jupyter notebooks are extremely detailed and are very easy to follow. The interviews with the creators and developers of the field at the end of each week's material are invaluable. Over all, this course and the others in this specialization are outstanding.

By Lachlan M

•Jan 22, 2020

A superb mathematical introduction to deep learning. Professor Ng and his team ensure that students gain a solid foundation in, and intuition for, the subject.

In my opinion, students will find they are able to focus on the deep-learning algorithms a little more clearly if they are already comfortable with linear algebra and basic Python. Therefore I would recommend taking a course in Python and having a look at basic linear algebra in preparation for this course or in parallel to it.

By Luis H G P

•Apr 19, 2018

Definitely the best introductory course I saw about Deep Learning! :) Andrew is a great 👨🏫 lecturer, always emphasising on the theoretical and practical concepts, developing first the right intuition about the topics to further tackle them with the formal approach and exercises in Python. Great methodology as well :) from the simpler to the more complex: it is almost impossible to be lost in this course!:) Thanks a lot Andrew and all the super team of this specialization!!

By Wagner F R

•Dec 27, 2019

Very good introduction to machine learning. The basic mathematical foundation is taught and we actually implement a NN from scratch with Numpy. In other courses I made backprop was just rushed, here we have the opportunity of see what is going on and then proceed to abstract it away and use the automatic mechanisms different frameworks offer. Thanks very much Andrew and all the assistant professor for the very 'deep' and well explained coverage of the NN during this specialization.

By Mathew S

•Apr 6, 2019

This class is a great overview of NNs. I have experience programming NNs using TensorFlow, which I learned how to do by following tutorials and using others' open source code. For me, completing this course really fleshed out my understanding and intuition of the internal workings of a neural network. Solutions for the programming assignments are mostly copy-paste-style, but one must think about the equations to do it correctly. Thank you Andrew, and the others behind this course.

By Тесленко С И

•Mar 23, 2019

The course is very, very entertaining. I enjoyed it. I liked your style of presentation of the material and its selection. To be more concrete, that's what I liked most:

+ Practical Assignments

+ Your explanation of hard topics in easy way

+ Deep Learning Legends interviews

Andrew Ng, thank you for the interesting, informative course! I can't stop watching your exciting lectures and solving interesting tasks and quizes. And now I am going to continue my Deep Learning Specialization!

By Baurjan S

•Jan 17, 2018

Very well paced and great in terms of digestibility of the course material. The first course, given you have no issues with the Python syntactics, will help lay the foundation to the principles of deep learning. The bonus of every week is an interview with the stars of deep learning and neural networks. I am lucky I took the course several months after it's been commenced. So there are no errors and it's been a very smooth experience. Looking forward to starting the second course.

By pasquale m

•Aug 26, 2020

i didn't expect an online course to be so well made. i'm an automation engineering student, so i'm interested in detailed maths explanations, and the level of detail of this course is very good. although i would have preferred some more details on some arguments and calculations, that i had to research and compute myself, i understand that this course is not intended strictly for people with strong mathematical background. Congrats to the developers of this course and thank you!!

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