Last part, part 4 needs improvement.

the lectures of last week r very bad

strong beginning, weak ending.

It is not that much effective.

T%his course is purely basic.

good course but expected more

too superficial to be usefull

1st 2 weeks were very basic.

Great mathematical analysis

Can I get a Certificate?

Needs more statistics

It is too low level

Good for beginners.

Fantastic teaching

Very useful course

toshkent

Yaxshi

Good!!

Yomon

good

No

n

Actually the lessons from first three weeks are really basic (junior to senior high level), and sometimes I can't find any strong relationship with data science. And the fourth week is about probability theorem including the marginal/joint probability and bayesian theory without introducing other fundamental concepts, which could make the student quite confused sometimes.

There are several typos by the first teacher, which most are all corrected but quite disturbing. And the handwriting of the second professor is sometimes sloppy. I'd rather check the "video companion" before taking the class. BTW, they are really good and concise to summarize the concept and understand what the professors are talking about.

About the quiz/exam, most are good with explanations. But a lot of question require electronic calculator. Some question do not provide basic value of number like log(2) or which is quite annoying.

It's not good as imagine, but it does not take much time to finish.

Weeks 1 - 3 can be understood with relative ease depending on your math skills. Week 4, however, is quite tough because both the instructional videos and the notes are difficult, if not impossible, to understand. I had to resort to resources both within and outside of coursera to understand Week 4, specifically YouTube, Khan Academy, free math tutorial videos from my public library, and a separate course on Coursera. I spoke to customer service, but they were unable to give me some sort of credit, or free month, or anything.

Coursera, if you're listening, please do a better job at quality control. Just because a professor is from a top university does not mean he can teach well.

This class fails to give a single explanation as to how the math skills will apply to data science. The first three weeks are a nice basic explanation of some of the math that will be needed. If you haven't done coding before or have some background in coding, you will have no idea where this class is going to be applied. The fourth week is the worst explanation of probability you can imagine -- opaque derivations and almost no explanations. I do not recommend this class as it fails to address the "why" of the title -- how does math apply to data science.