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 Francisco M R O•
Jan 08, 2019
The third and fourth week were a big leap in knowledge and not really well explained, for me.
par Mohammad A A•
Mar 11, 2019
It was a very useful course with some meaningful homework. My only criticism is that sometimes the theory and the practice are not well connected. Particularly the discussion of PCA, hierarchical clustering, k-means clustering and others. It would be benefit by providing more meaningful reading for those interesting in better connecting the two
Mar 10, 2016
The course content applies to R. The teachers focused on the programming language rather than the application of the existing graphs to explore data.
par Erkan E•
Jun 24, 2016
I wish there several comprehensive examples of exploring some real data as guided by the course instructors.
par Andrew V•
Jun 10, 2016
The course covers very limited subset of plots and mostly oriented to R-specific technical routines rather than overall approaches. Case-study example is helpful and contrary to the most comments I do appreciate the final course project: this how most problems are stated in real life. If you would like to cover more fundamental concepts behind exploratory analysis I would recommend other sources.
par Ray O C•
Dec 29, 2016
The first two weeks were good. The third was a bit confusing and the 4th one just felt like padding. A more in depth study of ggplot would probably be more beneficial as I felt like we were only scratching the surface with it
par Andreas S J•
Oct 04, 2017
Important and interesting stuff - but lots of it is repeated too much, which make it seem like 4 weeks is too much for the material.
par Haggai Z•
Aug 27, 2017
unfortunately this course was not in the same class as earlier courses
cases presented were not interesting or self explained.
concepts were wage and the lectures were boring
i think i need to take parallel course for the same knowledge targets i want to really understand this
par Amit O•
Sep 30, 2017
faced many technical difficluties in pratcice exerices in swirl
par Dylan P•
May 13, 2018
I would have liked an assignment to focus on the clustering methods and I think dimension reduction was reviewed way too quick.
par Ralph M•
Mar 09, 2016
Good course overall. There tends to be many lectures that are just lists of commands. Also, they don't seem to be updating the material. Many lectures are several years old and still have typos in them.
par Thomas G•
Apr 26, 2016
A lot of broken swirl(), which wouldn't be so bad except *a lot* of this course is based entirely on swirl(). Also the swirl() text was almost verbatim of the lectures one has just watched.
All in all, good information, but the swirl() badly needs an update.
par Sandeep D•
Mar 10, 2018
Excercises are very good. But I believe lecture could be more interesting and easily taught.
Feb 05, 2017
Course is good in general but "HIERACHICAL CLUSTERING" part is hard to understand and is not clear, should be explained more.
par Erwin V•
Mar 12, 2016
Interesting stuff, but not a lot of detail
par Jose O•
Feb 11, 2016
Insights delivered by the course were great. However, I think it emphasizes too much the lattice and basic plot systems to the point it is redundant with functionality on ggplot. It should focus more on concepts and techniques for delivering richer and meaningful graphics using ggplot rather than talking that much about technicalities on the basic plot and lattice systems.
Assignments were too basic and don't reflect all the concepts learned in the lessons e.g. clustering, which I think are of great interest for researchers.
par Gianluca M•
Oct 13, 2016
A nice introduction to the three plotting systems in R. The second part is devoted to clustering, but it is not detailed enough to be really useful.
par Ashish T•
May 05, 2018
Great introduction to the plotting libraries in R and visualization of data.
However the introduction to hierarchical clustering, and Principle component analysis was extremely vague.
par Ahmed M•
Aug 24, 2016
The course is quite good and informative in the first two weeks covering a lot of information and a lot of exercises.
Week 3 is very unrelated and hard the videos and exercises are bad, and I had to do this part by myself again.
Also when we get to the final course project doesn't cover any of these techniques.
In my opinion, week 3 should be replaced with something more related to plotting systems and distributions, also one project would be enough.
par Toby K•
Mar 01, 2016
Excellent overview of plotting and clustering. However, there were a few bits that were required for good completion of the projects that weren't covered in detail. Overall an excellent course and specialization.
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.