The course appears to assume good competency in Python and does not provide much training on Python. This should be highlighted to students upfront.

I am new to Machine Learning , as anew student I find the course simple to understand. I need to work on my lab skills which I will finish slowly.

Course is very well structured. Some extra guidance and assistance would be nice with the Peer-graded assignment as it gets bit tricky and complex.

Learned a lot in this course, I would've liked there were more exercises throught the videos rather than some questions at the end of the section.

There were a couple of videos where the notes weren't separated with punctuations. But other than that, it was a really good course. Thank you.

Useful overall. However some of the topics and concepts were not explained in good detail. Also there is some ambiguity in the test questions.

This course is very well, but it doen't have model selection and stratified features selection with sklearn.model_selection.train_test_split.

It was an awesome experience to learn machine learning. The instructor has explained every algorithm in a detailed way. It was very helpful.

good for an introduction to machine learning. the material could have been a lot more deeper on the various algorithms and when it is used.

Good course if you have some basic knowledge of Python and data analysis. However, much of the course material had typos and small errors.

Un curso muy completo, aunque mejoraría un poco los ejercicios, que al estudiante se le diera más importancia en la resolución del programa

It's so bad when someone reviews your assignment and gives you an unfair score. But this happened a lot because of this peer review system.

Well Explained. Video lecs are very easy to understand and upto the mark...Assignments little bit need more clarification and explanation.

I prefer if there is a human instructor rather than the machine one... Any way, great course.. it gave me the basics needed in the field.

I needed the syntax to be explained in the video tutorial also because it would be even easier to make the notes on a specific algorithm.

Great course ! I really liked the fact that you don't need to install anything to try out the code and the system works without problems.

The Course Could have been a little better if there were more theory and more illustrations at time a disconnect was felt in the Course

I think the methodology is outdated. But the bases are the same. It is remarkable that they teach how the algorithm and formulas work.

Very fascinating course but exercises like final project will be more for exposure to real coding than it will be really more helpful.

Course content and presentation is really good! The only thing i would add is the tuning of hyperparamaters which makes ML what it is.

Great course but there should be videos where there is need of explanation on code as well, codes given are very good and covers basic

I really liked the course content, way of teaching and assignments.

This will definitely help a beginner in data analysis to start with

Very nice course!! You learn a lot more of the theory than the practice part, but the concepts are well explained and I learned a lot

A good course to quickly learn important aspects of ML with Python. The assignments and final exam is also very useful for learning.

quite good at the explanation and un-graded exercises.

But the knowledge could be deeper and more about parameters in Sklearn APIs.