This course was taught at a much higher level than I was expecting. Concepts were broad and vague. Would have loved to work on concepts in greater detail or with additional practice and application.

Course was well organized and the content was also too good. However, the course could include some more examples. Overall it was good to start our journey is machine learning and data science.

very good course. Cuts to the chase. I enjoyed it as the lecturer was clear in his explanations and also I think all the necessary and important statistical parameters were mentioned.

This is not an introduction to statistics, the instructor assumes students having some basic background in probabilities, distributions. However, the slides are very useful.

This was a difficult course to understand. I felt like there needed to be more examples and practice problems. I'm still not 100% sure how to calculate probability.

Extraordinarily boring videos; the professor has zero personality. Really made it hard to watch and be excited to do so.

while I believe challenges are a good thing, I think the course was too much for its 'beginner' label

Starts off as quite beginners-level, though the onslaught of formulas can be overwhelming.

it was ok for a general background refresh. I was expected more solid knowledge.

overall this is good course for learning statistics for Data science.

Content is good but pace is extremely fast towards the later weeks.

The course was good but there is a room to make it more good

need simplification of certain topics as anova p value

Quite ok but some concepts are not clearly introduced.

good course but should be given a free certificate

It was difficult at times viewing the video's.

it was a bit too complicated for my taste.

so technical for math focus

наборы данных не актуальны

needed more details!

Very good

great

so so

good