Highly informative course. I'm grateful for this course because it made me think about a lot of things I think I would've missed were I to just try managing an ML project for the first time. It's clear that there are additional considerations in ML projects that aren't present in standard software product management. I would've like if they had provided some examples on how a deep learning project (like photo identification) might be different than a simpler model like regression from the product management perspective. The other improvement I think would've been more actual multiple-choice tests at the end of each chapter - the "discussion" tests are helpful to a degree for thinking through the information, but you don't get any feedback on them. I'd actually like something that tests whether or not I'm learning the material as well. But overall, for people who are genuinely dedicated to learning about ML projects, this was a helpful course.

The peer rating for the final project is interesting, if someone who does not get what is being asked for the final project is going to rate my final project. Saw some interesting examples.

I found this course more useful than the first course in the specialization - it followed a better structure and spent the right amount of time in various aspects of managing the course.

The course provides valuable tools for managing projects in this field. I am confident that I will use these methodologies in future projects.

It is useful, practical and has helped me complete many tasks

TRES BIEN

Good

Good

Ok

Very nice