The Course is a great start for anyone willing to learn. I loved the way the course was arranged which helped me understand each step and in the end the concluding programming exercise brought it all together for me. I personally struggled with Back propagation algorithm because of its complexity, however the way the course is arranged helped me understand more than I could if I studied it on my own. Thank you Deeplearning.ai Team.

I love this course the way it has been designed. If you want to go in middle or take videos separately it might be very difficult to understand and undermines the true value of the video. one must go from start and go in a sequence as the course is designed to understand the course. This course is much more about the mathematics behind the deep learning. I haven't seen any better deep learning course than this. Highly recommended.

Excellent course. The course teaches the theory very well. Even if mathematics is not what I am doing day in and day out, the way Andrew explains the theory behind NNs lets everyone follow easily. Also the exercises allow to practice the lessons learned. The programming exercises are very accurate and detailed. The instructors spend a lot of effort to perform tests and so make sure that one can complete the exercises step by step.

If you've ever wondered what goes on under the hood of a neural network, this is a great introductory course to take. As a layperson, I found the materials to be both informative and very accessible. The process of coding up the neural network components, assembling them, and then applying them to practical questions (I'm looking at you cat picture classifier) was really enrinching, and provided an extra layer(s) of appreciation.

This is really wonderful and amazingly useful course! Even complicated concepts are presented in a really easy and intuitive way.

There are some negative reviews about simplicity of assignments. This is not course to teach you how to program. Assignments are focused on deep learning concepts and we get to implement all of these concepts ourselves. Boiler plate code is already written for us, which i think is amazing use of my time!

This is the place to go to learning Deep Learning. Andrew is fantastic in explaining clearly quite complicated concepts by breaking down in small steps and putting it all together without missing the holistic view. He is very enthusiastic and passionate about the subject. I finally understand what a ANN is, understand the math, know how to implement one from scratch and can use what I learned to solve practical real word problems.

Eventually I get it!

I have written several times already the back propagation algorithm but never fully understood what was going on. It is not as trivial as it sounds but the notation, various and exercises make it very clear.

One of the best explanation so far. It really shows that Prof. Ng knows where students struggle and has understood what works in teaching neural networks.

The course made me smarter. That's a big achievement!

I really liked this course, as it was really up to my expectations and even exceeded it. This course contains my in-depth knowledge of Neural Networks from scratch and it helped me to know what includes the neural networks and cleared my fundamental doubt and misunderstanding regarding the same.

I thank deeplearning.ai for introducing their course on Coursera and I hope they keep making courses on the same.

Thank you once again.

The course has detailed content to implement the neural network and deep neural network. Also the comparison between 2 layer neural net, 2 layer deep neural net and L layer deep neural net can bring insights of the hyperparameters, forward and backward propogation. There is enough content to learn about the technical concepts behind neural networks and one can practically apply the same while submitting the practical assignments.

I was absolutely beginner in the field of deep learning with some knowledge of python and traditional machine learning algorithms. But this course has given me a broad view of the Neural Network and their implementations. I personally believe that Andrew Ng is the best teacher not just because of their teaching style but he always tries to give the maximum knowledge to their students even from the basic concepts.

Thank You So Much

An amazing learning experience in deep learning. Prof Andrew and TA's have curated a well-structured course. Basic knowledge of matrix multiplication and algebra was sufficient to understand the course work as said by prof. Andrew. The way he has abstracted the mathematics and provided just sufficient knowledge to understand the implementation of DL is amazing. (Going through his ML course will help further understand the basics)

the course is actually superb. very easy to grasp even the most complicated concepts. But, I did face just one problem that grading was malfunctioning in the second question of week 4 last assignment. my output was correct and matching expected output. but, still graded 0 / 50. I spent more than 8 hours figuring out the solution. And, repeatedly submitted same file 9 times, and it was automatically accepted and graded full marks.

Amazing course! I had taken a similar course in school but the amount of depth and ease of understanding in this course is phenomenal! Dr. Andrew has explained each detail with utmost simplicity, which even a newbie in machine learning can easily understand. I am so thankful to the creators of this course, that I got to learn and implement the very basic of algorithms to a L-layer deep neural network in this course! Thanks a ton!

Andrew Ng is amazing! Don't be intimidated by the theory, Andrew does a great job giving the intuition behind the theory, and you'll soon start to understand the theory by the end of the course. The programming exercises really do help internalize the concepts. I'm an experienced programmer, but not in Python, but that wasn't an issue getting the assignments done.

Thanks Andrew, for making complex concepts so approachable!

Prashant

When I first decided to take the course, I didn't have a background in machine learning nor python but I've immense love for the subject. After enrolling in the class I worked so hard for it, learned a lot from the mentors and other students on the forum. Apart from the subject matter I learnt how to be disciplined and work hard to achieve a goal. Thank you for the outstanding course - Andrew Ng and all deeplearning.ai community.

I enjoyed how this class held my hand and showed me how to code a logistic regression, a shallow learning network, and a deep learning network. I also enjoyed how their assignments gave me immediate feedback on my code via testing functions. When I coded for my DS certificate with Great Learning, I had to wait a week to get feedback on my output if I incorrectly believed that I had coded the functions correctly and proceeded on.

Thank you very much for providing this course. It was a difficult course initially, but as the course progressed, many things started getting clearer. Thanks to Andrew for the words of encouragement during the course. Hearing that If I didn't understand, I shouldn't worry and that I would learn in the coming lecture was what kept me going even if I wanted to quit the course. May you be blessed for helping people become better.  

Nowadays there is keras and tensor flow out there, making it easy to set up an DL project. But these feel often as black boxes. In this first class of the specialization, I like the fact, that a neural network is explained and set up from scratch. You'll understand the terminology, concepts and limitations as the knowledge is built from the start up. This feels very valuable as those tools will not feel like black boxes anymore.

It covers both the theoretical and practical aspects of neural networks really well. For the practical aspect, it does a great job of teaching you how to vectorize your code, which is very important in practice. The quizzes and programming assignments also did a good job of reinforcing the material. The programming assignments also had a good real-world application: image recognition, namely detecting images as cats or not-cats.

I think it was a really good crash course to NN with some good math insights. Andrew is really clear explaining the concepts and ideas behind NN. Having a good background on Calculus I would say this is achievable for people who is not familiar with it, without loosing too much understanding of what's going on.

The interviews with experts are really interesting, it's always good to know the story behing such great proffessionals.

A course for those that already know how a basic understand on how to build Neural Networks using high level API like Keras and want to know about the basic build blocks (and math) needed to really understand the way a neural network works. High recommended. Andrew Ng is an incredible professor, make the contents easy understandable. The lessons and questions are very good to check the whole content learned in the video lessons.

It's not a casual course, you should pay a lot of attention and take notes to accomplish. If you've never saw anything about Calculus and Linear Algebra, I think you will have much more trouble understanding the backpropagation. I think that this course gives you a good idea of how implement a neural network and how it works, but to be somewhat proficient you should practice by yourself a lot more outside the Coursera's Jupyter.

I wish I could use Coursera financial aid more( by paying 0 dollars). I really cannot pay anything (75% is not enough for me because I am living in Iran with terrible currency and bad inflation). I desperately ask Coursera to give more totally free courses for people in countries like Iran with terrible inflation rates. 1 USD in more than 500000 Rials of Iran, you can check that. Please. I desperately want some of your courses.

I knew a lot of jargon used in deep learning and other fancy words like gradient descent, back propagation but now I realized that those were simple and magical. Excellent course. All the way from a neuron to a deep neural network. Explanations were awesome, coding assignments were little bit difficult but interesting. I love the way Sir Andrew explains the difficult topics in simple words. Extremely happy to take this courser.

More detailed programming assignments should be given to hone the programming skills of the participants. The theory is mostly easy, Implementation of theory in python code is full of hassles and difficult. Error messages of python are sometimes unreadable and some extra help on common issues would help. Thank you, I am grateful for receiving such high-quality production videos and learning material from Industry Professionals.