Its amazing course to get deep knowledge of deep learning from the basics of logistic and Neural network.

The course has covered entire mathematical calculations. and if Somehow you don't understand the concepts at start, after coming to the week 4 you get complete generalized NN model.

Also, course assignment are amazing.

Thank You.

This first course in the Deep learning specialization is a really good one as all concepts are taught from scratch and give hands-on learning. It gives minute details and great understanding which is not usually present in other deep learning courses. Kudos to the instructor and teaching assistant for designing such a good course.

Good course. This course showed me a lot of intuitions to help me understand what a neural network is and how to build one from scratch. I used to think nn a very sophisticated model, but this course provided me an easy-to-understand way to enter the field of machine learning. It certainly also roused my interest in deep learning.

Excellent overview of neural networks and machine learning in general. This course teaches theory and practical in much detail, so that one can head start a ML project right away after finishing this course. For me it took away the fear of back-propagation and neural network coding. All thanks to Professor Andrew and his co-staff.

Andrew Ng is not only a leading expert in machine learning, he's also an excellent teacher - his courses are enlightening and informative, and easy to follow without being too difficult - how deep you want to go in is up to you as a student - you can either dive into the theory and equations, or simply learn the practical aspects.

This was my first course in Deep Learning. The course is very well planned and lectures are systematically put into place. As an introductory course to Deep Learning, I think this is the best course that one can take. All the concepts are explained very well before we get to assignment part, so it becomes easier to do it yourself.

Nice intro into Deep Learning topic. Explanations are really thorough and understandable for even those who know nothing about calculus! Assignments help to see the algorithms in action yet prevent you from getting swamped with technical details and from ending up battling against the grader. Can't wait to start the second course!

This course demystifies the black box of deep learning --but it is still fascinating. To be successful in this course, you'll just need to be able to code and knows how to do matrix multiplication (not the whole linear algebra). It's good to understand calculus too, but to pass this course (and get a 100% grade) you don't need it.

This course is good if you aim to have a basic knowledge about the basics of ML (which are very superficial) and an Introduction of ANN and DL. To get a better understanding of ML I suggest the ML Specialization courses instead, it's way much more complete and specific on several topics, such as Linear Reg, Logistic Reg, and etc.

This is beyond excellent. I think I started this about 5 years ago and felt overwhelmed, but the steady iterations and improvements are clearly visible as they encourage and build confidence in not necessarily knowing everything but walking away with intuition, the ability to intuit how to build NN's. Well done Andrew, well done!

I love the simple and practical explanations. All the concepts were presented in a way that helped me solve some of my problems with fundamental aspects of creating neural network models. For example, the part about the vectorized version of backpropagation or the difference between shallow and deep models. Thanks for this course

The way this course is taught is amazing. I left with a complete understanding of the inner working on Neural Networks, and I feel I am ready to tackle bigger problems. The attention to Mathematics is just right, and the practical tests are really, really good. I can't wait to take more courses offered by DeepLearning on coursera

I learned a ton. It was a very heavy focus on "translate formulae to code" which was a challenging refresher for someone 15 years out of college and having not used that skill set since college. The roughest parts of the class were a result of some Python idiosyncrasies and could be chalked up to inexperience with this language.

Excellent course! It is very friendly with beginners by explaining every notion intuitively, without skipping any dry theory. I would love it even more if the course forces me to think more when doing the exercises. The exercises sometimes seem too oriented (the hints are too close to the solution). Overall, thanks! Great course!

Excellent course which contains comprehensive instructions and practical guidance from Instructor. Really enjoy and have learned a lot from the course. Thank you instructor for wonderful teaching and TA for answering classmates' questions. Looking forward to learning more about NN and AI in Python. Best Regards and Blessings. Mei

This is a great introduction to the world of deep learning. For someone with a calculus and linear algebra background, this summarized perfectly what I need to know to implement neural networks efficiently from scratch, without skipping apparently complicated stuff like backpropagation, so that I can start creating my own models.

Very helpful in understanding the basic concepts of Neural networks. also the length of videos are very appropriate and discussion forums are quite helpful in clearing doubts. Assignments and Quizzes are very relevant. Overall I really like the structure of the whole course. And recommended for any beginner who has interest in AI

This is a great course for understanding neural nets. I've learnt a lot by going through this course. The best part of the course is that it encourages us to implement the neural network from scratch without using any high level framework which helps us to gain understanding of what's going on and how things are working actually.

Andrew Ng is the master in explaining deep learning. He mentions everything you should know, the practical side, the code as well as the theory. This course really helped me to understand what deep learning is doing under the hood. A must-do for any deep learning engineer! (And I am also glad he switched from octave to python ;-)

The course servers as a perfect intro into Deep Learning. If you know some Python coding, and even some theory or have previous experience in Machine Learning, but want some detailed explanation of the math or hands on coding exercises, its perfect for you. I love the content and can't wait for the others to open for enrollment!

I highly enjoyed the contents of this course as it allowed me to know about the math that goes into building neural networks as well as knowing how to build neural networks of any number of layers from scratch, this was an excellent course that i would recommend to anyone interested in diving deep in the field of deep learning !

The course, in general, was easy but high level. If you are new in the world of AI-ML and have familiar with some basic machine learning algorithms such as regression, this course will be the best way to continue. However, if you are entirely clueless about what machine learning is, you might find this course a little difficult.

I have been working with DNN for a while, and having this course made me have a deep insight into what actually happens. I did know what happens with the forwards propagation step, altought I was never really sure about the process that takes the backpropagation process. It helped me a lot to recapitulate and reinforce concepts.

The explanation for such complicated concepts is done beautifully. The quizzes and assignments are designed well enough to clarify whatever doubts might arise. This course keeps you invested throughout. Even the discussion forum for this course is very active and hence if any doubt arises, it will get clearly easily and quickly.

This course gives a great start for those wanting to understand neural networks and deep learning from scratch. However, if you are already using tensorflow, pytorch, etc, and are not into the details of how they work, this course is not for you. This is for those who want to know the things behind those deep learning libraries.