The course walks you through different effective ML strategies. I'm holding the 5 stars just because I expected to see some hands on assingments.

Overall a great course. Some of the quiz questions are very hard because the corre3ctness of some of the available options is quite a bit “fuzzy”.

The course has given me insight about the handling of ML projects. But it would be great if there was some CODING and specific algorithm involved.

Good course! Focusing on strategies on how to start well and manage a DL project.

But very vague! Hoped to have more thery & a usecase on the topic

I had some problems answering some questions correctly since there was no specific emphasis in the lectures and I was somehow unsure how to reply.

It has nice discussions on the practical aspects of Deep Learning projects, but I wish it had more Math, and it had more programming assignments.

Thorough and well taught course on strategy in ML. Would have enjoyed some programming exercises, but the assignments served their purpose well.

This course was relatively short, and the quality of the materials (lecture videos, quiz text) was somewhat poorer than in the previous courses.

Good practical advice. I would have added something about agile development and possibly practical advice on NN architectures (depth and size).

Excellent content but the quizzes are badly done, many questions have several reasonable answers and very little feedback if we 'get it wrong'

The course would have been more interesting if we had some programming assignments. Hands on experience into some of these cases really help.

Unique course in the sense that teaches important topics that are rarely seen in the literature and are fundamental in designing AI projects.

Had some pretty great info for junior Project Managers, for some reason, it's also hiding some extremely important info about end-to-end DL.

Course is a little short, only 2 weeks and a quiz. I feel there could have been another week added, with another interesting case study ,

Some of the videos weren't of good quality. Also, I was expecting doing a real project not to make decisions based on different scenarios.

This is an important course for practical purpose. It tells us about the methods to use for improving your model by doing error analysis.

Good course overall, would have liked to have the in-depth programming assignments though, those really made the other courses stand out.

Learned various ways to structure ML projects in industry.

It would have been great to have few programming assignments included as well.

Some tips are very useful for practitioners but the same information is repeated over and over again that makes the course quite boring.

A small course with very effective tips and tricks to figure out how to start and proceed further while building a project effectively.

I think this lecture is very useful when we make our own ML system.

Also, it has many examples about errors we can usually meet in real.

Useful, practical material. I probably underappreciate the importance of someone (especially of Dr. Ng's stature) covering this for us.

Very practical lessons in this module that should make you and your team more efficient in implementing deep learning on real problems.

another great Andrew Ng course. This one gives practical insights in how to go about making your deep neural networks perform better.

I really found the pilot training quizzes are great and very helpful, but some questions one can debate if has the right answer or not