This was really an interesting course which allowed me to build DL models from the ground up. It helps one to better understand what DL frameworks are doing in the background. Such a great learning experience. I would encourage anyone wanting to take this course to spend a week or so brushing up on their python and numpy to be able to move a little faster.

This is a great course. Especially, the teacher is brilliant. I have leaned the key concepts in deep neural network and know how to build a network by myself. The programming exercise is really helpful, where I could deeply understand the structures and connections for each part of deep neural network. The exercise help me better understand how it works!

Excellent course for beginners that want to explore deep learning. The course goes into the fundamentals of Neural Networks, starting with a simple Neuron to build a basic classifier, then using more layers to capture more complex functions, and finally creating deep representations to capture even more complex information from the data.

Highly recommended.

The topic "neural networks" originally spans only 1 week in the instructor's other coursera course "Machine Learning". Here we spend 4 weeks to deep dive into it, comparing logistic regression, shallow nn (2 layers), and deep nn (many layers). It is excellently taught, just like the other course; great coding assignments to deepen students' understanding.

The course has been a great learning experience. The fact that differentiates this course is that there was a balanced focus on theoretical concepts, mathematics, programming and real-world application. It was fun to code the functions from scratch rather than simply calling some built-in Python deep learning library functions in this introductory course.

This course gave me a deep understanding about the functionality behind the deep learning . I love the way Andrew teaches . You may find it hard in the beginning but slowly you will be feeling comfortable . I will recommend this course to anyone who is just a beginner . Take this course before taking any other course . This will accelerate your learning .

Andrew Ng is a legend, the thing I really liked about him and this course is that whenever you are feeling down about some topic, he backs you up at the end of the video telling you not to worry even if you didn't understand it completely. I think this phrase really pushes you to do more, and once you keep going previous things start to become more clear.

Very instructive course, with a lot of hands-on! Andrew explains in a very easy why, emphasizing the practical points, but always indicating the pathway for those who want to go also more deep into the math. I specially liked the interviews with the "Heroes of Deep Learning", they were very motivating. I highly recommend for those interested in the field!

I began after having finish Andrew Ng's Machine learning course and as a result, the first three weeks were quite easy. The programming exercises walk you through most of the problems, providing the relevant information as needed. Overall, I enjoyed the course and thought it was a good introduction to the topic, yet the assignments were on the easy side.

Concepts and intuition are clearly explained. The Jupyter notebooks are well-structured and contain a lot of additional helpful information and explanations. Furthermore, it's absolutely great that the notebooks are provided as a service. No need to install any software. Perfect! For me, the only downside was that the programming excercises were too easy.

For people that have experience with coding and decent background in math, this course might be too easy in most cases but also leave some questions unanswered in terms of deriving all of the results (you'll have to work through matrix calculus yourself). But you can speed through the lectures and assignments and get a decent foothold into deep learning.

If you have ever heard about this course from someone in the 'complaining' tone that 'It is of very basic level...' - for those, I want to say that - Whoever wants to understand fully the internal working procedure of a deep neural network, instead of just using the one line built-in function of a deep neural network, this is an amazing course for those.

great course for transitioning from the basic ML course into Deep Learning. Refreshes your understanding and application of NN from the basic ML course. Also, the assignments on deep NN will provide you with a strong foundation for more difficult DL concepts. (material be a bit too superficial for those who already have a strong understanding of deep NN)

Deep learning is used widely in present and Surely in the future.

This is the perfect place to study deep learning in-depth. Andrew Ng has done so much in the community of AI that learning directly from him is just a matter of luck.

So you think deep learning and Machine learning interests you.

You won't regret doing this specialization.

Love Andrew Ng sir

This course made me understand the basic concepts behind deep learning. Deep learning idea is really simple. Using multiple hidden layers (more than 2) for better accuracy makes neural networks think deeper. So this course is around deep neural networks (DNN) only which makes it easier to connect yourself with machine learning world very easily and fast.

Good course for beginners, but video camera quality is too bad. Need to recapture the endings part where Andrew speaking in front of camera.

Second bad part is wrong formulas for dZ2 and dAL where (1/m) factor is missed. Instead of being included into derivative of last layer,

1/m scale factor propagated into formulas for dW and db, which is totally wrong.

Course gets right to the heart of the matter and uses modern electronic lab book methods via Jupyter notebooks. And the calculus involved is introduced as a refresher so one doesn't have to dust off the calculus texts to understand the math. It was also fun to see video interviews of "Heroes of AI" to get the history behind many of the techniques uses.

First course I complete on coursera. This course is at good pace if you have machine learning basic knowledge, and is very suitable for you to leverage your small trunks of time. The course projects are very well-designed to give you hands-on experiences on how deep learning works. I'd recommend this course to anyone who wants to dive into deep learning.

I have never seen such a well organized and thoughtful training. The classes were made as simple and yet concise. The quizzes were tailored to beef your grasp of the core concepts. The programming assignments? Fantastic, makes sure all the concepts taught were represented and understood and provides tools and leverage for a go in the professional world

Excellent! This is the fist time, I found a practical use for the math skills I learned at the University. The course finds exactly the right balance between theory and practical applications. I liked the exercises a lot. They were challenging and strengthened the understanding of the theoretical knowledge in order to transform it into practical skills.

Very interesting course - I did it two times. Second time around things were much clearer - first time I went through it very mechanically. It may still be very challenging to do all the assignments from a scratch. i.e. how to set up this kind of process from a scratch. The template followed is a very good one. How to build up the solution step by step.

Thanks to Andrew ng and deeplearning.ai. Course topics are nicely aligned with a very good and detailed explanation. Overall course gave me a good intuition around neural nets and related math.

I personally liked the idea and thankful to deeplearning.ai for giving an opportunity to Deep Learning enthusiastic to hear thoughts from heroes of Deep Learning.

A good learning with all the necessary basics of neural networks and deep learning, especially enjoyed the tips and experiences shared everywhere in the courses by Dr. Andrew Ng.

The assignments are very helpful yet the frameworks are not totally implemented by the students so it is definitely necessary to go back and review the codes every now and then.

This is a great course over all. Andrew never fails to simplify the complex. Note:If you're thinking of taking this course, then I advise you to familiarize yourself with classic machine learning (you can take intro ML courses on Coursera, Udemy, Udacity or EdX for free) and python programming. Having these basics set will make your experience seamless.

This course was one of the best course that I attend there. The most interesting feature of the course was simplification of advanced concepts so that I could learn all of them without any complexity. Also, assignments were not only a simple assignment, but also they are a way to learn more. Many thanks Dr. Andrew Ng to provide this excellent course.