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Very informative and concise. Perhaps assignments could have been a bit more hands-on, but hey, it's only two weeks course!

I learned a good set of tricks and tips. Thanks!

I was able to understand the important design decisions that surrounded at each stage of learning and learn about impact of errors in deciding the future course of actions

For me the best course of the specialization right now (I haven't done 4 and 5 part yet). There is a lot of practical knowledge. I really like Heroes of DL in this course!

Gives a really good understanding of how to solve issues at different stages of ML project's lifecycle. Good for people who have spent sometime working on ML/DL projects.

Just like the preceeding two courses in this specialization, it was great. Andrew can really transfer his knowledge in a way that makes it very accessible and applicable.

It's incredible that Andrew Ng shares his real-life DL experiences to help ensure beginners know the key factors to consider to much more efficiently work on DL problems.

This course taught me how to handle real life problems in neural networks and flight simulator exercises are good for understanding concepts clearly. Thank you Andrew ng.

Very essential topic, professionally handled by Mr. Andrew Ng. Thank you all for your efforts, you are start-to-end covering deep learning. Hope i can continue with CNNs.

This course was pretty useful and related to the problems that one faces in real life situations and projects and provides a great methodology to deal with those problems

The courses helps me understand how to work in a real machine learning projects. It does not have any practical coding part, but at least the information was good! Thanks

I really liked the format of the assignments for this course. Case studies are incredibly useful and give a global understanding of the different aspects in a ML project.

The course gives hints on how to structure and manage a deep learning projects, on which parts to put priority first in order to efficiently use time to get good results.

Again, such an incredible course! I really loved to learn startegies from the experienced Andrew Ng. This helps me shape my ideas when working on ML projects. Thank you!

I learned a lot of strategies from this course regarding pitfalls and how to better structure machine learning projects. This is really valuable experience from experts!

Really good course that any ML (future or present) practitioners to learn. In my opinion, more important to learn than the other technical courses in the specialization.

A very interesting course, no doubt afterwards you will be able to structure a machine learning project and know how to evaluate the different factors that influence it.

This course packs a lot of highly valuable practical knowledge. It has helped me a lot in applying DL better in practice and save a lot of time when creating new models.

Excellent practical advice on how to make quick decisions when faced with a dilemma during ML projects. The simulations really help bringing the course material to life.

Extremely practical. Much shorter than other courses in Deep Learning specialisation but definitely not less informative. I also enjoyed the Flight sim a lot, nice idea.

The material presented here is greatly useful. Learning these concepts by own require a lot of year of experience. I wish more details were presented about each concept.

I personally enjoyed this class (especially after the second class in the specialization) and I will definitely be using some of the knowledge soon enough. Thanks again!

This course gives practical aspects of problems faced in machine learning projects. You must have knowledge of these ideas if you want to compete in fast growing world.

The most fun and intuitive course in the deep learning specialization. Amazing literature by prof Andrew NG. Would suggest every practitioner to go through this course

One of the best courses of DL specialization. The knowledge shared is invaluable and it is tough to get such good insights elsewhere. Thanks to Prof Andrew Ng and Team.