Y
Sep 23, 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!
CC
Jul 28, 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.
By Tim B
•Dec 29, 2016
good intro
By Johnnery A
•Nov 17, 2019
Excelente
By Khobindra N C
•May 18, 2016
Excellent
By Rohit K S
•Sep 20, 2020
Nice!!
By Tae J Y
•Mar 31, 2017
Good!
By Edward A S M
•Dec 5, 2019
Good
By 木槿
•Nov 2, 2018
good
By Anup K M
•Sep 27, 2018
good
By Isaac F V N
•Apr 18, 2017
Nice
By Chan E
•Mar 22, 2016
nice
By Adur P
•Dec 28, 2017
A
By Saurabh K
•Apr 27, 2017
G
By deepak r
•Oct 2, 2016
d
By 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.
By 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.
By 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.
By 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
By 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
By 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
By 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.
By 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
By Toby K
•Mar 1, 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.
By Ralph M
•Mar 8, 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.
By Shorouk A
•Oct 22, 2021
The course only provide how to use the tools technically, but not statistically. also the only hands-on complete project is peer-reviewed, which means we don't get to know what we need to improve, etc.
By 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.