Good to review some concepts if you have an Intermediate level of knowledge and excelent if you're new to the area. Still very light on mathematics, but the course is excelent

Very good didactical approach. The labs are straight-forward but test programming skills more than AI expertise. Editing and error checking in the notebooks is poor.

Very good learning experience. Bit difficult than the previous course on supervised learning, but concepts can be understood if we listen and understand carefully.

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

its a very good course to understand basic concept of machine learning. sometimes its hard to understand the code. otherwise its a 5/5 course.

It would be much better if you link a relevant applied AI course with this package. The course is more of theory, than practical application.

Explains the working behind algorithms well . But you need to spend time actually building some projects with this knowledge on your own

Pretty great. I kind of wish the assignments were a little more challenging but I realize that it's a beginner level course too.

The last week is less boring, it was hard for me to grab to concepts of the last week, it seems everything magically works!

The course is very informative but assignments solutions are provided. There is a lack of challenging learners to do more.

This one is a little pacy compared to the first one. Maybe the explanation for the math is not as clear as the first one.

Really good course, maybe some more project-like assignments would be beneficial to assimilate the concepts more deeply

If the lab materials and implementations were described It would have been the best course on Machine Learning Basics

Great material. I felt there was a lot of talking, but it might just be me. I do better in a hands-on environment

Concepts are well explained, but the last Practice Lab had confusing problems that were not well-explained.

Amazing Course!! I feel that the Random Forest and XGBoost section could be a little more elaborated.

I wished they added neural networks after all the ML algorithms but agains the teaching was amazing

The labs are not very challenging, maybe some more coding would help to understand more material.

i needed more practical projects and code explanation but theoretically the course is very good!

I found the lab practice a bit simple and technical on one side but not intresting on the other.

course is good, content of the course is easy to understand but their is a lack of practice set

This course is really interesting and the lecturer explain each topic very neatly and slowly.

The only thing this course lacked was a capstone project/ direction on how to practice

It should have more practices. There's a lot of theory, but just a little practice.

More labs would have been nice especially for non initiated student in Python