Clustering topic is covered superficially, too much time spend on employing ggplot graphs, not very useful since making graphs is straightforward on other software, like excel, once you aggregate datasets correctly. I had not found it very enriching as a course. I would merge this class within R-Programming section and call it Part 2 rather than categorizing into "Exploratory Data Analysis".

Some parts of material is good quality, but some is bad - also some show bad practices in R. Extensively use swirl as assignments over self work. It is better to go through good tutorial over R base plotting system and ggplot2.

The final project did not require use of the material in the course beyond the first week and a half. I did not take any quizzes or otherwise have my knowledge tested on the material in the second half of the course.

Course content and assignments were difficult to follow. Loads of statistical content along with high-level R content means it was probably the toughest of the 4 I have taken so far in the Coursetrack.

some swirl tests (4,5) don't work because of parameter method in qplot function. This parameter is not realy existed in this function now

SVD should be better explained. I found diffucilut to understand. Some backgroeund matrices and it's operations should be explained.

Quite repetitious in covering basic graphing, and very shallow in regards of clustering, SVD and PCA.

Very unprofessional, compared to other courses. It wasn't well organized.

About plotting in R. Not about generating real insights from EDA.

Too weak regarding the clustering methods, very disappointed.

didnt get much useful-- a whole "course" on plotting? meh.

Not upto expectations

too superficial

Veyr boring

NEEEEEED TO EDIT MY PEER REVIEW FROM OTHERS

Material is to basic for an entire course.