Coming in a dev who doesn't use python, I really liked the course. The lessons are good. The first lab is easily the hardest part. I wish there was a bit more on numpy and matrixes before the first lab. It gets significantly easier with each week as they build on eachother and you get some repitition with forward and backwards propigation.

A very good course for those who want to understand the basic concepts of neural networks and how to implement a simple net using Python. I really appreciate the math explained in this course. It is very helpful for a person with little mathematics background like me. Also, the programming practice is useful with lots of detailed explanations.

I've been through so many courses in deep learning, every single one of them either starts with Keras or some other high-level framework. But this course touches the very bare bones of Deep Learning and forces you to implement Logistic Regression to a Deep L layer neural network completely using Numpy.

Prof. Andrew Ng is a great teacher indeed!

In my opinion, this is one of the best course to get you started right at the point!

Too many people complaining about the programming assignments but if you were a complete beginner to the world of ML (and even noob at Python) like me, you would have been grateful instead. Thank you Prof. Andrew Ng and Coursera Team for this wonderful course.

Great overall. I came in with a very basic understanding of Python, but had a deep understanding of the math and stats from Uni so managed to follow the lectures relatively easily.

I would say that a deep understanding of the math/stats is not needed, but it definitely helps. Especially when it comes to visualizing what the matrices look like.

Final assignment was challenging but worthwhile. This is a good introduction. I would still recommend implementing these things on one's own, because the "sandbox" that Coursera provides is kind of... limited... but it's a good, fast introduction to neural networks, and you do have to kind of understand how they work to implement it quickly.

An extremely friendly course in deep learning (basic feedforward neural network), even those without background knowledge in calculus and algebra can get ahold of it.

Although if you're CS major and have sufficient math knowledge (in terms of an STEM student), you may need extra challenges to get deeper into deep learning.

Well worth the price.

Great course on the fundamentals of Deep Learning from DeepLearning.AI taught by none other than Andrew Ng. It was very beautifully designed to cover forward propagation, backpropagation, gradient descent, and all other fundamental deep learning concepts like layers, nodes, activation functions, parameters/hyperparameters, and cost functions.

The course really drills into the maths behind ML and Andrew Ng breaks it down into very understandable chunks. My only recommendation would be to ensure your Python is pretty solid beforehand as the course does not guide much with the scripting for the assignments so if you do not know Python well you might get quite lost at times, as I did.

Forever in awe of Professor Ng's style of instruction, learning has never felt this fun and rewarding! This course gave me a whole new perspective on some of the things I know about deep neural networks, and was a great start to the Deep Learning Specialization. Eagerly looking forward to taking the rest of the courses in this specialization!

I've completed another great course by Andrew Ng. After his ML course, this was a pretty good neural network revision and practice on Python. I can't express how grateful I am to Andrew and Coursera's team to provide these great courses for students who need financial aid options. Hopefully, I'll pay for these great courses once I find a job.

It was amazing. Andrew sir is really good and this course is also made to be understood by non-AI professionals. I wanted to know about the basics of AI, so I took the basic AI knowledge course called "AI for everyone". Then I found myself interested in learning more. so I took this specialization. Thank you for helping me gain AI knowledge.

Have gone through few online courses on this topic but left all of them midway cause i was not getting the insights and in depth math background of neural networks that i desired to acquire but this course designed and taught by a legend just overwhelmed me with more than what i expected..A great course for stepping into deep learning..Thanks

Amazing course by Andrew NG. Topic was made very interesting to help develop understanding on how NN/DL works . Really liked the Implementation structure that focused on designing and developing the modular structure/functions to enable building own network, rather than on programming. Looking forward to further courses in the specialization.

This course gave me a lot of insight into how neural networks work bu going in depth into the math behind these structures. I am a type of person who doesn't like to use libraries until I can understand the code and what it does and this course allowed me to transition into using libraries like tensorflow without going against what I believe.

If ML/DL is highly sought after skill in the industry, then definitely this course should stand as highly sought when compared with every other courses available around the globe. To me, highlights are the deep knowledge that Prof. Andrew posses, and the way he presents. I believe it took lot of efforts to prepare all programming assignments.

I took this course to gain intuition in how deep learning works and I achieved my learning objectives. Andrew's teaching style is just amazing. You have to get the concept provided you pay attention.

I have learned so much in this course and I am looking forward to achieving great things in the world of AI today.

Thank you Andrew and team.

I am a person who wants to know all the details so it took me a little while because I was busy looking at derivations and reasons for why we use non-linear activations etc. That aside, the course is very to the point and the programming assignments are amazingly helpful. I can't recommend it enough! Plus you get to make a cat identifier ;)

1.After week 2 , did not received any quiz inside the lecture video . {those are really useful.}

2.Keep an option to add notes rather than taking screenshot/recording .

3.keep an option to comment in between lecture and direct towards discussion forums , basically keep discussion forum as a open sidebar for every lecture will be great option .

This course is a great head start for a beginner to deep learning. The concepts are explained clearly and the programming exercises gave me the confidence to learn further.

A few suggestions: Please include pdf files of the lecture slides for reference. Kindly try to ensure the matrix multiplication compatibility while writing all equations.

Thank you very much. Your teaching made me understand more. But sometimes I feel that it's a little too early . What I like the most about this course is the exercises. You can design the exercises very well. At first I was determined to study the only free course. But now I change my mind, I want to study all of your courses

Best regards

It's an amazing introduction to neural networks and one of the best courses I have seen on the subject. Most courses ignore the maths behind neural networks and just focus on the coding part of it. This course went into the right amount of detail helped me learn the fundamentals really well. I hope to build upon it with the upcoming courses.

While all explanations of material are very clear and nicely presented, there were a couple of things I did not like:

1)While this specialization was designed to be standalone, the first course is completely covered in Andrew's ML course.

2)Too much time spent discussing logistic regression

3)Programming assignments have too much 'hand holding'

I really liked this course. It gives you a good understanding of what deep learning ist. The videos are very good. The only thing I have to say is that I felt the programming assignments were a bit too "follow the recipe", didn't allow too much "self-thinking". But I did get the chance to try a lot with the code I wrote after I submitted it.

Great course ! However, word of advice, do not underestimate the level of complexity. Make sure to listen to the lectures at a least a couple of times and dedicate at least twice the amount of recommended time. The lectures are excellent, and the homework and assignments are well organized and really does help understand the concepts better.