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!
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.
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 Ratnikov Y•
May 27, 2017
Clustering is overwhelming field of knowledge.
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 Pavel B•
Feb 18, 2016
I like the course and it was helpful in understanding how graphics work in R.
par Saruul A•
Dec 23, 2017
good for building basic foundation
par Phillip K•
Mar 20, 2018
Good stuff just as I have come to expect from this University and the courses that are part of this Signature Track.
A great deal of the lectures and work on assignments/quizzes/projects was learning and using the various plotting systems in R. Certainly this is important, but to put it into perspective, I spent four hours creating six plots for the final project, when I was able to use Tableau Desktop to create all six plots in under five minutes.
So formally learning the data exploration techniques was good, but expect much of this course to be about learning the R plotting systems.
That said, there is a point in this course (and the first time for all the courses to this point) where the topic suddenly got very, very technical. When clustering techniques were introduced it felt as if you were turned on your head as the focus suddenly went from various ways of plotting data in R to being neck deep in the explanation of clustering techniques that require a great degree of Linear Algebra knowledge.
Don't panic though. While there are questions in the guided assignments that are difficult, you don't really need to recall all of your Linear Algebra courses from college to pass this course. After all, R "has a package for that."
par Paul M•
Jun 02, 2016
Very good introduction to the various graphing systems.
par Greg R•
May 31, 2016
Pretty good course. Nice content. Middle section on clustering felt random.
par Vebashini N•
Nov 14, 2017
Thank you, i learnt a lot and will continue on my journey.
par Giovanni M C V•
Feb 16, 2016
Excellent course with great didactic. Congratulations!
par STEVEN V D•
Dec 08, 2017
Great practical course on exploring big datasets in R. The main part, plotting, is very clearly and thoroughly explained and framed. Only 'single value decomposition' and 'principal components analysis' was somewhat hard te grab and need a lot of extra research and study.
May 23, 2016
Apr 25, 2018
Nice course, very useful. I wish the links were updated more often, however.
par Lindy W•
Nov 24, 2016
Interesting learning more about ggplot and base plotting system, as well as clustering techniques.
par Bijan S•
Jan 30, 2016
The course is useful with a lot of learning.
The second half needs more of improvement, I think the pace is quite fast compared to others.
par Jeremy O•
Mar 10, 2017
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 Chan E•
Mar 22, 2016
par Carlos L•
Jun 22, 2016
swirl is very used in this course. It is one of the best tools to learn R
par Prathamesh N•
Jul 09, 2017
SVD & PCA videos need improvement in terms of background knowledge and understanding
par Irmgard T•
Jul 23, 2017
great course...though I would have preferred less focus on cluster and k means analysis.
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 Chun-Fu W•
Jun 21, 2016
Very interesting and insightful course. I enjoyed it.
Assignment was okay, could have provided more challenge and depth though.
par Zhang S•
Jul 09, 2018
Week 3 content is difficult to understand without background knowledge in clustering and component analysis. Hope the instructor can provide some materials or web links for cluster and component analysis at the beginning of Week 3. Other weeks' contents are good and helpful!
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.