Very well organized. Gave me plenty to think about. A few questions in the beginning were a bit rough (correct answer was not necessarily the correct answer)

The lectures were very good, but the labs can be more beginner friendly,and coded in such a way so that one doesn't only depend on hints to complete the labs

The Course is really good for theorical content, however I feel it might be lacking a little bit of practice.

The quizzes/ tests are really easy to pass, too.

Pretty useful, but I would have liked to seen more practice examples with actual code. I believe having someone to walk you through a lab is more beneficial.

I've understand the concept but here want add up on a lecture like how to implement those algorithm in python it will be easy to understand for a beginners

The course was pretty hard. But the quizzes in the middle of the videos rly helped. I would recommend a bit more help with the python aspect of the course.

The lab work should not be fully solved. Or program should be left with question, formula and method explanation. Answers could be given after submission.

very good course but it needs lab practice , it looks like we just run the code , aand if we want to write by our self it is hard . but thank you so much

Great introduction into machine learning, but I wish there were more options for practice rather than optional labs that are already completed for you.

This is a nice course. It gives a nice introduction to machine learning. The instructor is very nice at explaining concepts in easy to understand words.

The course is great and would have been much better if the optional labs had also been explained for a deeper understanding. Thank you for this course.

It is pretty good yet i wished if they made the optional labs not optional and concetrate at code live implementation, Anyways thank you NG for sharing

It was a bit too easy. I would have preferred more practical insights into the coding of these algorithms, as well as the theory behind the algorithms

thank you for this great course

in practice lab you do 30% from code and this is noot good you need to do 70% from code and they only 2 practice lab

Very nice explanations. Even for people that already had machine learning as course I filled a lot of small gaps in my understanding and knowledge.

Could use a bit more rigor in the assignments, but I appreciate the entry-level nature of it. Making ML accessible for most (realisticaly, not all)

I think it was a really good beginner course, but frankly, a bit slow at times (maybe a bit more could be added to really make it 3 weeks of work?)

Andrew's explanations were clear. I wish the course had a project or a homework assignment at the end of each week to have more hands-on practice.

This Course will would become more and more intresting and best if with concept explaining and CODE explanations of optional lab both will happen.

great course but recommend learn phyton or a little math and stats first also made some basic project in phyton so that you can understand labs

It was really good course.

but I preferred if it has more challenge to implement all the programs by ourselves and teach more about the codes.

Excellent course. I had a bit technical difficulties with the notebooks. Error tracking is not as easy as in the system I ussually work with.

use scikit library as mandatory not optional. add lab that use the functions immediately not need to edit them. or use predict immediately.

I would like to suggest to add lectures and explianations on importing libiraries and scripiting alos to amkemit more robust and independent

Everything it very well taught. In practice labs instead of utils another library should be used as it cannot run apart from their notebook