The discussions on practical guides about designing deep learning systems, dealing with data, bias variance trade-off, and how to organize projects to optimize time usage are much needed for practitioners.

Practical advice for new students when tackling a real-world ML project and how to approach to optimize a model's performance. The quizzes provide good examples of use-case scenarios and decisions to take.

I think the simulations were great. They give an excellent approach to real life enterprise scenarios where you have to take important decisions. Great compliment for the first two courses of the program.

Step by Step approach to structure Your Machine leaning project from scratch. The cherry on the cake is simulation quit provided at the end, helps quite fast to get the practical approach to the problems.

This course is very helpful to fine tune our machine learning and our deep learning projects and probably more input to the different types of transfer learning examples could have been much more helpful

I love it. it was very helpful but I think if it was an assignment "programming assignment" with some issues "mismatch, incorrect labeling, .. etc " and use those techniques it would be much more helpful.

Its most great and important course ever, please try to listen very carefully to Prof Andrew, he tell you about each and everything you need to become master in ML. Many thanx for Prof Andrew and COURSERA

I really enjoyed taking this course. The use cases and practical strategies to the problems were really insightful. I'm really excited to apply what I learnt from this course on my own personal projects.

I learned a lot of new methods to structure not only deep learning projects but also ML projects. Very interesting and gives a wide overview of how we can improve our project management in AI in general.

Excellent course - Andrew's teaching is what's so needed in the machine learning community. He explains concepts properly so that one truly understands them, and thus knows what to do when applying them.

Prepare you for the problems faced in machine learning projects, I'm now capable of analyzing projects for other people although I'm only in the path of Machine learning for 40 days.

Thank you, Sir Andrew

I believe Andrew Ng shared some key insights into building successful machine learning projects. I really enjoyed the course and believe the shared information to be invalueable for my further research.

This is the most important course of all the machine learning courses from deeplearning.ai. I learned in two weeks, what normally will take years of experience from this course i.e. ML project strategy.

Well structured course for structuring machine learning projects. I've looking forward to go more with similar learnings. It is very helpful to expand an idea. Shortcuts with projects are promised here.

That course is so valuable in order to drive into a ML project. Especially, the project life-cycle simulator are really awesome to practice model diagnostic and what to do next !! Really amazing module!

A very unique and practical-based course that really shows the intricacies involved in making a machine-learning project and Andrew has really provided with hardcore lessons from his enormous experience

Course is really useful in explaining which part to focus on to reduce the error and how to detect which part of algorithm should be given more time to reduce error and improve performance of algorithm.

A bit more theoretical this time. But the information is worht the time. I think that the knowledge Andrew is spreading will make me more efficient in my AI jobs ahead. At least I hope and think that :)

Andrew Ng's excellent teaching style leaves you with an intuitive understanding of machine learning setups and potential pitfalls. For me it's the best way to learn; this stuff really sticks in my head!

Incredible course, so full of practical advice from Andrew Ng. Ah, and speaking about transfer learning, I cannot stop surprising myself of Andrew's ability to transfer his learning from him to others.

Very well structured course about all the little tuning things to be done to actually make a machine learning algorithm work well. It is really a course to be taking as part of an overall ML formation.

Really interesting!

We used to be concerned about unbalanced train/dev/test, and with this course I realised this are not the main problems for achieving performance in ML

A master class.

Thanks Andrew!

not as technical as the first 2 courses in this specialization (and the next 2 for that matter), but it is still a well rounded course and highly recommend to do all the courses in this specialization!

Extremely interesting and useful practical advice that can help make significant difference when thinking about how to identify and correct problems. The quizzes were fantastic and made me think a lot.

Excellent material. I would say this is the most important course of this specialization. Knowing how to approach a certain problem can indeed save us a lot of time and help us avoid a lot of mistakes.