This course is really great.The lectures are really easy to understand and grasp.The assignment instructions are really helpful and one does not need to know python before hand to complete the course.

I have learnt a lot of tricks with numpy and I believe I have a better understanding of what a NN does. Now it does not look like a black box anymore. I look forward to see what's in the next courses!

Amazing course for anyone wanting to jump in the field of deep learning. Andrew explains the details very well. The assignments were structured very good that provided detailed instructions. Thank you

One of the best courses I have taken so far. The instructor has been very clear and precise throughout the course. The homework section is also designed in such a way that it helps the student learn .

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.

It's really quite an amazing course where we get to learn the mathematics behind the Neural Networks. It is great to learn such core basics which will help us further in developing our own algorithms.

Very structured approach to developing a neural network which I believe I can use as foundation for any project regardless its complexity. Thanks professor Andrew Ng and the team for their dedication.

Too slow, a lot of repeating facts, very little contents in total in the course, and nothing new compared to the old machine learning course which was more fun and much faster. Nice environment with python notebooks though!

Meh. I don't know why we are spending so much time in Week 2 talking about the math and how to not use FOR loops in week two when he STILL hasn't given any kind of overview about why we do this math, how we're going to use it to identify cats in pictures. Instead, we're just yakking on about math math math math math with NO context whatsoever. If I wanted a math class, I would have taken a deep-in-the-weeds math class. I expected a higher level of instruction for this higher level of abstraction but instead it seems that he just wants to talk about math and how to use vectors in NumPy. Zzzzzzzz.

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.

I think that this course went a little bit too much into needy greedy details of the math behind deep neural networks, but overall I think that it is a great place to start a journey in deep learning!

I did the ML course from Andrew Ng before and it was amazing, which is why this course was so disappointing. It should've been named "Casual Deep Learning" rather than "Deep Learning Specialization"

Programming assignments were ridiculous, they literally had the answers on the notebook you're working with. On top of that the grader doesn't work properly either, so what's the point even?

I had prior knowledge about deep learning but the course was so repetitive that I feel like it would even bore a beginner. Andrew Ng talked about the same matrix multiplication and derivation processes over and over again and how important they are, while at the same time reassuring students that it wasn't a big deal if they didn't know calculus which I strongly disagree... If anyone wants to learn deep learning they should at least understand _the basics_ of calculus, linear algebra, probability and statistics. I understand this is an online course and level of entry isn't very high as there are many people from various backgrounds trying to break into the industry but still I feel like downplaying the importance of a good mathematical foundation is giving people false hope.

This course is really quite bad. I'm not sure why the rating is so high. Probably because they are only prompting people who completed the course to rate it.

The main problem with the course is that It spends the majority of its time describing a byzantine set of notation while avoiding actually helping you understand how to apply the concepts you're learning. So you learn that a^[l](i) is the activation vector for layer "l" and example "i" but then you get to the python portion and, big surprise, none of that information is even slightly useful.

Even worse, the course hasn't chosen its audience. If you're good at math you'll be annoyed about the math explanations. If you're good at programming you'll be annoyed by the programming explanations. Rather than isolate that material in a way that lets people skip parts which they already understand, you get a really basic explanation of everything all globbed together.

Anyway, I'll still try to hack through this thing to finish it, I'm just letting you know that if you're underwhelmed, you're not alone.

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.

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.

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.

Excellent course !!!

The flow is perfect and is very easy to understand and follow the course

I loved the simplicity with which Andrew explained the concepts. Great contribution to the community

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.

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

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

not satisfied

Great Presenter in Andrew Ng, on a topic of tremendous interest to very many.

However, unfortunately the grader seems to work only rarely in accepting submissions. Code that runs perfectly in the Notebook is repeatedly rejected by the Grader. Dozens of comments on these problems when the course opened two months ago. But still the problems have not been fixed!

And if you want to reset your Notebook for a fresh start , that may take hours or even days .

A pdf addressing exactly what one needs to do would be sensible. Instead one spends dozens of hours trawling round Forum discussions to guess what might actually work for the Grader. A most disappointing experience. Why is this considered in any way acceptable?

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.

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

Too easy