Greate course! Andrew Ng's method of teaching and the way he conveys concepts and ideas are awesome, and you will get an intuition about neural networks. Related programming assignments and applying the mathematical theories you learned in the course into a real-world problem help you understand the concepts even better.

Amazing scaffolding to get from linear regression to deep neural networks. I do feel I am missing some intuition about the theory of what is happening in each hidden layer, but I have a solid working knowledge. The audio/ video could be better quality. I would 100% recommend this to anyone interested in learning about AI

This is the best course and specialization on Deep Learning I have done so far. Absolutely loved the content and teaching methodology which covers the basics to the most advanced topics, providing elaborate and intuitive understanding. Looking forward to learning much more.

Thanks Andrew Ng, Deeplearning.ai and Coursera.

Excellent course for those who are interested in understanding what exactly neural networks are and how to train parameters in a neural networks. I really liked the way how logistic regression is used to make us understand neural networks.

Looking forward to learn existing topics from other courses in this specialization.

A very well oragnised course, I really appreciate the way Andrew sir teach concepts . Anyone who have little knowledge of python, calculus and a pinch understanding of matrix properties can easily understand the concepts highlighted in this course. It's my first course on coursera and I really appreciate it. THANK YOU!!

This is a very good course with gradually improving difficulty, which made me learn a lot new things from a totally different persepctive. This course also improved my skills on Python programming, which is a very good introduction learning of Python. I get a lot of interests now and I will learn the following 4 courses!

It's a very interesting basic deep neural network course. And now I can understand the base of the deep neural networks. There are many useful informations in the python implementation such as vectorization optimizing your codes. I knows more about the AI technological trends throughout the AI hero videos in this course.

I have done other courses on introduction to the deep learning and found this course to teach things in a mathematical way. The professors reputation precedes him. The assignments were the best so far which are guided and focus on getting the concept ingrained and not focussing on the programming errors that might occur.

Learning experience was awesome. Hadn't seen any course yet in which each and every concept is explained from the scratch. Every fundamental from a single neuron to L-layer NN is explained in a very simple language. I appreciate the efforts of Andrew NG sir that he explained the concepts so well and in a easy to get way.

Prof Andrew's instructions were very clear and succinct. He also managed to put the deep learning concepts across in an easy to understand manner. The programming exercises were also well structured with sufficient comments for guidance. Overall, definitely 5 stars and look forward to taking more courses taught by him :)

Very good course. The programming assignments are good but are too tedious. Check out the book at "neuralnetworksanddeeplearning.com". His code makes more sense and relates better to what we are trying to achieve. All that work related to storing things in caches and making dictionaries of the parameters seemed wasteful.

Really helpful to get started in deep learning. If you were good at math, such as linear algebra, probability, that's ver y helpful for you to understand the deep learning, but it's still ok if you don't know much of math, since this serial courses has hide some math knowledge and reduce the difficulty when you learn it

The course was excellent. The explanations in the slides by Andrew Ng was very simple by anybody to understand. Quizzes made us to think and revisit the weekly videos again. The programming assignments were very systematically designed to cover all the concepts of NNDL from scratch to Model and then for an application.

The course is fantastic. It clears your basic (although it is a good practise to have a basic understanding of NN before your kick start this course). This course lets you understand the real mathematical picture inside the NN and help you build your own NN with any high level APIs - pytorch, tensorflow to name a few !

Great course. A lot of contents are mostly refreshing what was learnt in Machine Learning. It does skip quite a lot of ML content, which will be explained in the next Deep Learning course. Suggested to really finish ML by Andrew Ng before going through this course or beginners might get lost of what he is talking about.

A great introduction to neural networks (NN) and deep learning. The instructor, Andrew Ng, clearly knows his beef. The course is light on derivation and focuses more on the applications of NN, which is a good way to get people excited. I learned a lot from studying the way Andrew Ng sets up the programming exercises.

this course was very amazing and really enriched my knowledge in neural networks and i liked the programming assignments a lot, it's really cool to apply the stuff i learned and i am planning to make it far with it , i'll dedicate my future to deep learning .

I want to thank the professor Andrew for this amazing course.

Fantastic Course!! The concepts are made as simple and easy to understand as possible and taught with the best quality. It really helped me getting to know the concepts of neural networks from the depth and understand its working and implementation. Also, the educational interviews for each week were pretty insightful.

I have spent days to find such an amazing course which instruct basic things of Deep Learning for newbies. I am really into this course and find out that it is completely suitable for those who want to learn DL from scratch. The instructors also explain all intuition of formulas which is the aspect I appreciate most!!!

I learnt the basics of Mathematics used in neural networks in this course. Being an M.Sc. Mathematics student myself, the concepts were explained in an easy to understand way, while also exploring the very nitty-gritty of mathematical concepts used. I look forward to doing more courses and completing the specialization

This course is already very good. Teacher gave me a better understanding of python programming and neural network. Only one thing can be improved. If we can get the data set and make the model totally by ourselves, that will be amazing. Overall, this course is good enough and I will do some extra work after the course.

This course does a good job expanding on the neural network content from the instructors Stanford Machine Learning course. It does a good job demystifying concepts like back-propagation and the change to Python with NumPy from Octave/Matlab makes the coding exercises much easier to read and applicable in the workplace.

A great introduction, has been pretty easy for me especially since I have already done the Machine Learning course offered in Coursera by Andrew Ng. This course shows simplified implementation of real-life data science projects and image classification, and also provides lots of tips and tricks from the masters of ML,

Really the main challenge of this course to implement codes with appropriate dimensions. I liked how it was made very clear during the instructions. There is one point in the backward propagation in deep part of the implementation where dA of the previous layer is indexed by the current layer. That was a bit confusing.

I had some issue with the automated (I assume) grading system. Aside from that, I found the course material to be very informative, and the assignments both challenging a representative of the material covered in the course. I look forward to continuing along with the rest of the courses in this track. Thanks so much!!