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 Glenn W•
Mar 02, 2019
I really enjoyed this course. I was a good reminder of what analysts need to do when looking at a new dataset. Dr. Peng does a great job walking through the steps and there is enough information given to enable the student to effectively explore on their own.
par Ryan B•
Apr 25, 2018
Good, but the lack of assignment in week 3 seemed to screw up the UI, prompting me continually to do the Swirl exercises, which were non-compulsory (and, given I hadn't completed any of the other Swirl exercises, something I didn't want to take on.)
par Guilherme B D J•
Jun 09, 2016
The only missing point I would say about this course is how to deal with skew data and/or outliers. Although it is not specific to "cleaning data", I think there is a good opportunity there to at least give some hints on this subject
par Rashaad J•
Aug 28, 2017
The Swirl activities followed along with the lectures, which allowed us (as learners) to better understand core concepts. The lecture videos continue to end while the professor is still speaking, but this is not a major issue.
par Ashish S•
Apr 02, 2017
It was awesome to learn visualization. SVD and PCA part of the course could have been elaborated better, and a pilot project on that would have cleared the basic concept. As usual Prof. Roger is a engaging and amazing teacher.
par Mark F•
Mar 27, 2018
The course was great, I'm not sure if I'd really consider using the base plotting package in reality as the plots are just too ugly, and the API is harder to learn. I think a stronger on ggplot would help to keep it relevant.
par Connor G•
Aug 14, 2017
I enjoyed the course and learned important graphing concepts for R/RStudio. I just wish the assessments had been a little more rigorous, as it felt like I could have done better but still passed the projects anyway.
par Greg A•
Feb 22, 2018
This is a very good course, at times it felt like the instruction was to do things mechanically without understanding the motivation. Perhaps this should come after or in conjunction with Statistical Inference
par Carlos R•
May 29, 2017
I love the course. However, the treatment of PCA, SVD, and colors seems to me very long and slow. Maybe a more direct and quick overview would be better. Even with that expection I really enjoy the course.
par Bill S•
Jun 21, 2017
The course on Exploratory Data Analysis was highly enjoyable. I used to do a lot of this sort of thing in my job, but now spend more of my time managing people. It is fun to get "hands-on" again.
par Raviprakash R S•
Feb 14, 2017
Nice course, but too much focus on "R" as a tool.... Industries don't use R as much... The course must be made more generic and independent of R - understand it is not easy to do but ....
par Luke S•
Nov 01, 2019
Good introduction. The swirl exercises kind of reproduce the lectures though- felt like it might not have been the most efficient use of time to go over the exact same example again.
par Ng B L•
Mar 09, 2017
When it comes to hierarchical and K-means clustering, the theory wasn't explained clearly. When do we use U and V for what purpose? How does D come in? I'm left confused after this.
par Štefan Š•
Apr 17, 2016
I found it very useful.
Some space for improvement are better coding skills (naming variables) and
some more complex topics like SVD / PCA should be explained in a more intuitive way.
par Diego P G•
Jan 07, 2018
It's a very good course. Week 3 was a little bit more challenging than expected, as well as assignment 2, but you get a good idea of how to use all the different plotting systems
par Christian B•
Dec 11, 2016
The course is interesting and the content is relevant. I do think that there are some issues with project 2 though. I did provide feedback on that to the course administrators.
par Hernan D S P•
Mar 06, 2018
I learned a lot on this course, it helped me to understand and identify some of the situations I experience at work. Totally recommended if you want to apply it right away.
par Terry L J•
Oct 18, 2018
Seems this would type of course in an online learning MOOC would be better if it was more direct hands on "how to" and less focused on explanatory fluff (academic style) .
par Igor T•
Jan 30, 2017
Good introduction to patterns recognition. I found principal components analysis technique very useful. It would be great to provide more lectures about this topic.
par Diego T B•
Nov 17, 2017
Interesting. But I would prefer the differences between comparison plots. What do they are useful and why is it better to plot with bars rather than lines.
par Robert W S•
Feb 14, 2016
A quiz or project question on k-means clustering or PCA would be nice. Overall the course provided solid coverage of the three main plotting systems in R.
par Guillaume S•
Jun 08, 2018
Interesting course to know plotting systems and to have a first view on clustering and dimensions reduction. This part should be however more developed !
par Hyun J K•
Apr 17, 2018
Great lecture. I hope there were more assignments. (1 per a week maybe).
I learned many statistical concepts and rcodes by taking this course.
par Robin S•
Feb 28, 2017
The course was fantastic. It was very challenging. I could do with some additional opportunities for exploratory analysis to reinforce some concepts.
par Steven C•
Mar 15, 2017
Good course on plotting libraries and useful plots in R. Wished there was more coverage of ggplot and less on lattice, but overall a useful course.