Less good than expected. Explanations could be more clear.

I don't like the example and the explanation at all.

Great material, but could be better organized.

really bad review criteria for grading peers.

Heavy content to cover in such a short time

Most lessons lack clarity. very evasive

The stuff is very high leveled for me.

Would be better if taught with Python

Learnt many new things. It was good.

Hard subject, hard explanations

Difficulty level is high...

Its good but not too good.

Too mathematical for me

The lectures were Dry

Good, Productive

a bit cursory

Too complex

Too sparse.

Very basic.

A hard one

no passion

A lot of the concepts in Stats Inf - although simple when you think about it and used pretty much every day - I felt were difficult to understand at first. Wikipedia and some other online sources, and youtube videos, were more helpful but I think the real issue lay in the teaching style. I won't knock Mr. Caffo like some of the others here have because at the end of the day everyone learns differently. What works for some might not work for others and unfortunately his style did not suit my learning requirements.

My rating is purely based on the content which I think can be simplified by giving more visual examples. I am rating this after taking the 'Regression Models' course and in that course it is MUCH easier because he gives "real time" and visual examples of what, eg Residuals, mean or represent. Just that alone made a huge difference and it then helps me focus on how to write the R code rather than trying to understand the math. Hope this helps!

I am left feeling this course needs work. I don't know if it's the pain of switching to the new platform or what, but the total lack of any support from the TA/instructor team is frustrating. Add to that the fact that Brian skips from slide to slide very quickly often not providing adequate explanations and you'll be re-watching the videos many times over.

Several of the videos have blatant errors in them, like the fast that the fourth video of a week also contains the entire third video... again.

Such things should not have passed a half decent QA test.

More than anything this specialization should not be marketed as "no previous experience needed". You need to know some statistics. And by some, I mean do the whole thing on Khan Academy first.

I get this course since I really want to learn on boosting. However, I think the course pace is too fast and should be include more 'non-greece symbol'. I have a background in biostatistic and epidemiology but I'm still having a hard time understanding lecture. I would say that this course is the most difficult among this specialization (practical machine learning is much easier than this). I bet many students will have a problem in this course since it's a 'beginner' level specialization.

My suggestion is to 'slow down' , expand the lecture with more drawing/picture explanation, more r coding and get rid of those greece-symbol as much as possible.

Connection between the slides, transcript, R code, and pdf presentation slides and the text book is great! Easy to follow along. Concepts are explained poorly. Often definitions are missing and the student has to guess what is meant by a variable on the slides. Very superficial learning. Not nearly compareable to real university course. I think the students would benefit from more project work assignments and peer reviews. This is when you really learn something - when you have to do it yourself. Quizes are a good start. I did the course as a refresh and I can't imagine correctly understanding the concepts just by having completed this course.