Programming assignments are really good. In general, I got to know from people who code that you don't get to know what's happening in the internal neural network structure if you're using a python library, but here, I got to learn each and every step/block in the code as well as in the lecture videos. I thank Dr. Andrew for his great explanation of mathematics associated with neural networks. Looking forward to catch up with the other courses.

This course contains a lot of mathematics and provides a thorough know-how on the inner complexities of Neural Networks. Sir Andrew is very thorough and provides convenient notebooks with guidelines, making it easy enough for the intermediate Python-er. However, it would be advisable for beginners to cover the basics of machine learning before delving into deep learning, in order not to be overwhelmed by the sheer amount of technical know-how.

I believe that gaining knowledge is the most purest and beautiful thing in this world. To really understand how this world, or how to solve the simplest of the problems, knowledge is a very important factor. Andrew Ng has a way with explaining core concepts to really make the student understand the topic in the most simplest way. He explained the concepts and empowered an individual like to me to understand and fall in love with Deep Learning.

Gives a very good overview of NNs and basics of DNNs without getting too deep in the math (not needed for implementations) while also providing enough intuition (usually in the option videos) to satisfy my curiosity. Also learned about matrix and vector handling in the Python numpy library with concepts, such as broadcasting, being explained thoroughly. Having examples using Python idioms really helped with becoming a better Python programmer.

Great introduction to artificial intelligence and more specifically neural networks. The great thing about this course is that it both covers the math behind it (although not too deep), as well as hands on experience in the form of coding neural networks from scratch. Both shallow and deep neural networks are covered. To succeed in the course, you only need to know a little bit about linear algebra and calculus and basic programming in Python.

This course is absolutely amazing. I work as data scientist already and took professor's Ng first course on machine learning.

The topics are really well explained and the assignments well thought out. They are not very hard so you would be discouraged to keep at it but you still need to understand concepts really well to finish.

Since I love calculus, I also derived the equations from first principles to compare the results.

Amazing jobs guys!

This is an incredible starting point for Machine Learning. Every thing is explained in a detailed and understandable manner. Neural Networks and algorithms like Back Propagation have been taught in an easy to understand and intuitive way, while also delving sufficiently deep into the mathematics of it all.

I used to think that Andrew Ng's Machine Learning course was the best one there is, but somehow this manages to better it. Simply brilliant.

This is a great course to start learning machine learning/deep learning, and while it is aimed at beginners some background experience with Python definitely helps. In four short weeks (or shorter, depending on your bandwidth) the course goes through creating logistic regression models, to shallow neural networks and then to creating deep neural networks. The programming exercises are very well structured, and Professor Ng is a great teacher!

People having a background in ML may find this a little too easy. Perhaps, easier than it should be. Much on the lines of ML course by Dr. Ng, this course does not delve deep into mathematics. I recommend this course for those who wish to focus on implementation, but not necessarily math.

That said, I have looked at other MOOCs for DL, and found this to be the best. Unfortunately, none of them go deep enough into math, and understandably so.

This course is fun. Also, Andrew Ng is a good teacher, calm, he goes straight to the point. I have problem watching a teacher who is over-hyped or with tic or are filmed too close to the camera. In other words, I lost my focus when the teacher get my focus on himself and not on what he teaches. So, Andrew Ng is the perfect teacher for my kind of learning. He keeps things simple and he seems to try to be low-profile and this is excellent.

Excellent course. Must for all AI enthusiasts !!! It taught me how to do programming in python. It has removed my fear of Programming which is biggest take-away for me. Machine learning concepts and Deep learning Fundamentals will become crystal clear post this course. Happy to learn this course. Will complete Deep Learning specialization. Thank you Prof. Andrew Ng and team. Excellent Material, Excellent Delivery and Happy Learning to all

The course was structured with an incredible amount of organization. Also, the course taught the core of deep-learning implementation, as opposed to focusing on the theory, which takes a significantly longer amount of time to understand. Understanding the theory is important for thorough understanding, but there are other platforms for learning theory that are also very good.

It was a pleasure to learn from Andrew Ng! He is a great teacher!

This is very a good course for the beginners and it provide understanding to the maths behind the deep neural networks & and a good understanding to deep learning. Explanation about various topic is provided in Clear and Concise way, interview with experts and pioneers in DL is something very amazing . this course provides amazing understating for building Deep Neural Models, theoretical concepts and math is also beautifully explained.

Excellent and effective approach that fairly mixes the conceptual and practical parts of ML/DL/AI. Well organized course content and instructor is easy to follow! Suggestion: should there be any need for the course admin to update the notebook like what happened during the first part of the last assignment, it would save students a lot of effort and wasted time trying to figure what happened if the admin would communicate prior to acting...

The couse is great in quality and pace of the learning about DeepLearning. The lectures cover the material and question that I immediately had along the lectures were noted to be covered in next courses. The asssignments build intuition about how calculaiton work and how the graphical algorithms are implemented in practice. The programming part is to be leartn outside of this course as it mainly focuses on delivering DeepLearning concepts.

An extremely exciting-to-learn course. Particularly recommended for all newbies (like myself!!). The way course lectures and assignments are structured is amazing. I have one suggestion. Assignments have been pre-filled for the most part. I feel that maybe letting the student write the other parts of the code as well will give him better confidence. Otherwise, it is tough to have proper take-aways from the coding assignments. Thank you Ng.

This course was an excellent introduction to neural networks. The optional content allows students with greater familiarity with calculus, linear algebra, and regression analysis to leverage those skills to attain a deeper understanding of the topics, without alienating those who want to focus solely on being a practitioner. I would recommend this to anyone with an interest in AI and at minimum a basic understanding of scripting in Python.

Lessons are very clear and well explained. The best part though are the assignments which are clearly organized and help to put in practice what you've seen on the lessons.

Couple of things I would think could make it even better: Optional videos for math derivations (not only intuitions), coding example videos, and some case studies example videos to see how everything fall is applied before diving into the practice exercises.

Thanks David!

This course helped me understand what Neural Networks and Deep learning is. Don't worry if you are an absolute beginner, I started with 0 experience as well. The layout of the course is very different, it starts from the very basics and everything is crystal clear. I learn more in 7 minutes of Andrew's Video than reading for hours elsewhere. I recommend this course for anyone wanting to start learning NN and DNN. Go for it! Its worth it.

I have been wanting to understand deep learning for a number of years but was always worried about my Python programming skills not being good enough, and my understanding of mathematics needed not being solid either, and this course really builds up one's understanding of topics gradually, taking time to explain things step by step. Andrew is wonderful. Comes across as genuinely interested in my success as a student. Thank you very much!

I used to be into machine learning and neural networks back when I was a master student around 1999-2000. This course was a great way to refresh some of that old knowledge, and also introduced me to many new concepts that were not widely known at the time, such as vectorization and the new activation functions. I loved how the python code already had the framework set up, allowing me to focus on the main learning points for each exercise.

Great course with laser focus on deep learning essentials. Covers linear algebra, Python matrix operations, and key material for a solid foundation in deep learning.

Anyone who has taken Andrew Ng's Stanford Machine Learning course from Coursera will find this course fairly easy with regard to the core content, but they will also benefit from the singular focus on deep learning in Python.

The homework was actually both fun and instructive.

I gained pretty good basic theoretical understanding of deep learning by creating models from the scratch using numpy. Mathematics was also presented on the appropriate level needed to understand how it really works. Unlike Microsoft or other courses, there was no statements like 'this is a certain mathematical fact but we won't dive deeper into it..'. It was also good to refresh linear algebra using numpy which sometimes can be tricky.

A beginner friendly approach to learn the inner workings of Neural networks. The curriculum is neatly divided into weekly classes, which are not very had to complete in a week. The videos are also the right duration to facilitate revisiting difficult concepts. Each week's quiz and programming assignment are very helpful, well-designed and focussed on reinforcing the concepts. A great course. Highly recommended. Thanks to Dr. Ng and team.

The quality of this course is rarely seen on Coursera. It painlessly presents the necessary skills and knowledge to build a (very) simple deep neural network for image classification, assuming no prior knowledge. No need to pause the video to decipher slides, no need to search the web to find extra information, no diving into forums to find the errors in the tests.,...This course will turn your grandmother into a machine learning expert.