Jul 29, 2016
This is the second course I have taken from Roger Peng and both were outstanding. I have a strong math background, but not much of a background in stats, but this course was very approachable for me.
Sep 24, 2017
Very good course! It provide me the foundation in learning how to plot and interpret data. This will definitely strengthen my "R programming" to generate publication type figure for my genomics data!
par Guy P•
Mar 26, 2016
It misses an assignment which will allow to practice the clustering skills.
par Alex s•
Jan 17, 2018
It focus too much on the tools and a little bit on the analysis
par Johnny C•
Mar 06, 2018
In general was good, but there were some lectures and exercises which were disorganized ("plots with colors")
par Casey B•
May 12, 2016
Good class - links and slides have not been updated recently. Frustrating to finish without the exact linkts to the data.
par Katharine R•
May 03, 2016
Good course, but the SWIRL exercises (and a few quiz questions) needed to be updated for the latest version of ggplot2.
par Fabiana G•
Jun 23, 2016
Course feels somewhat abandoned by instructors. Content is okay, but can't help the feeling that it's basically a cash cow - students would benefit a lot if instructors were move involved.
par Rafael A•
Mar 23, 2017
First two weeks are too repetitive with other courses
par Samer A•
Mar 30, 2018
It's pity that the final assignment doesn't involve the clustering and the principal component analysis. It was quite a demanding topic and I was looking forward to practicing it through solving tasks.
par Mehrdad P•
Aug 26, 2019
The course was overall ok, but I wish discussions about k-means, PCA and SVD were divided into two courses.
par Arne S•
Aug 31, 2019
did not like the swirl-tutorials. they were very tedious and sometimes labelled correct commands as false (e.g. when you typed = instead of <- for assigning a value to a variable)
also I was surprised that for a beginner programming course in R you had to apply specific functions such as grepl without the function being introduced in the course
par Daniel P•
Dec 08, 2019
I've learned plotting in R. I expect to learn more in four weeks of "Data Science" specialization.
par Pamela M•
Jun 05, 2016
Alas, after only 10 minutes of the first video, I am reminded that this instructor does not gear his lectures to the true Beginners among us. He speaks much more for an audience of grad students. I do want to complete this Specialization, so I will try again perhaps after learning more - about statistics and R and who knows what else. I fought my way through the first three courses, but now I'm going to work smarter by finding other ways to acquire this knowledge. Then return to him; maybe. This course should be labelled Intermediate and Statistics should be listed as a prerequisite. (I think; since I don't know what it is that I don't know, I am making a guess as to the missing piece of the puzzle.)
par Rohith J•
Dec 14, 2016
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.
par Tamaz L•
Apr 05, 2016
Very unprofessional, compared to other courses. It wasn't well organized.
par Piyush V•
Jun 21, 2016
par Joseph M K•
Jan 31, 2017
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".
par David I•
Mar 26, 2016
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.
par Dmitry R•
Feb 06, 2016
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
par ewa b•
May 31, 2017
didnt get much useful-- a whole "course" on plotting? meh.
par Desmond W•
Oct 19, 2016
About plotting in R. Not about generating real insights from EDA.
par Michal K•
May 10, 2016
par Bartlomiej W•
Feb 06, 2016
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.
par Freddie K•
Apr 05, 2017
Quite repetitious in covering basic graphing, and very shallow in regards of clustering, SVD and PCA.
par Lidiya G N•
Apr 29, 2019
Absolutely No technical help, like insane amounts of homework for each week. People have jobs and businesses to run. Incredibly short duration. Like literally this should have been spread out several more weeks. I would have dropped the class but I can’t. It’s so difficult to get i to the first set of practice assignments and these several sets. Honestly, I am literally getting no help on it and probably won’t pass because I am missing the deadline. I finished 5 coursera courses working on them for 24 none stop. I’ve literally been at this class all day. Besides all the insane amounts of assignments there’s tons of videos to watch and uploads to do. Go buy some books or take another class unless you are unemployed or have nothing better to do.
par Jamie R•
Jun 07, 2019
Just an extended course on using R. There was little strategies for Exploratory Data Analysis, infact the example jumped from a high level view of the data to then start looking at individual counties. There are multiple tools in the market that will deliver in a better and faster way for exploratory data analysis. This course should be more targeted at developing a skill set that is tool agnostic.