Content is good. Presentation could have been better.

machine learning project are highly iterative as you.

I miss notebooks for practice, besides questionnaires

If there is some coding practice, it would be better

Very well explained but needs more reading material.

It is an unique lecture providing empirical advises.

Great set of guidelines. Mostly theoretical, though.

Concrete reminders of important and practical points

Very useful materials for leading a ML research team

interesting insights about real world implementation

would like to have more excercise related to coding

Would've liked to have some programming assignments

Introduced a lot on engineering project experiences

Very interesting topics were shown in this course.

Very useful knowledge that is not commonly taught.

Interesting but perhaps we could have gone deeper.

Is the flight simulator hw going to be added soon?

Great course. I liked the compact, 2-week format.

A little bit abstract. But still very inspiring!

Very interesting tools and ideas for applied ML.

There is so much noise in the explanation voice

Not as strong as the other 4 of 5 of the series

Great course. Needs deeper practical examples.

A lot of insights rather than technical details

Coding exercises would be great in this course.