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 Daniel R•
Mar 03, 2016
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 Stephen G•
Sep 22, 2016
Overall a good course!
par Christopher L•
Jul 24, 2017
great intro to the plotting system. could be better with a dimension reduction assignment or quiz. this is very important!
par Philip E W J•
Mar 21, 2017
Would have needed a litle more in depth explanation of the clustering analysis
par Ratnikov Y•
May 27, 2017
Clustering is overwhelming field of knowledge.
par Ankush K•
Jun 15, 2017
Useful for learning how to make plots, but not too detailed. Further analysis would have been helpful.
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 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 Adur P•
Dec 28, 2017
par Migdonio G•
Apr 10, 2018
You should give more datasets for independent practice! Something we can play with.
par Harshitha R•
Feb 22, 2016
The course did a good overview of the different plotting systems in R, but it rushed through clustering. I had to watch the videos of k-means and hierarchical clustering at least 3 times to sort of understand it. The matrix concepts went completely over my head. Otherwise, the projects were very interesting, and I would highly recommend this course to other people.
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 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 Jeff B•
Mar 04, 2018
The plotting aspects of this course appealed to my visual sense.
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 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 Praveen K B•
Sep 14, 2017
Good One to start with
par Chuxing C•
Dec 03, 2015
I have taken the course earlier, so am somewhat familiar with the layout and the materials. Overall it is a very good course and covers a wide range of subject matters. Roger has done a very good job explaining the concepts. I certainly would recommend this course to all who's interested in the subject.
I realize that there's limitation on the time people suppose to spend each week, however, I would like to suggest adding homework, in addition to quizzes.
Several video clips have some audio issues, not sure if that's fixable.
par Subramanya N•
Dec 12, 2017
ggplot should have been given more emphasis. It warrants a course on its own!
par Pierre D•
Feb 03, 2016
More challenging Problem sets, as in the R Programming course !
par Deepak R•
Oct 02, 2016
par Ruggero B•
Feb 29, 2016
My congratulations to all those people who worked to create this course although I have to pick up something I've found a bit annoying:
1- there were two video where the audio were nearly unintelligible
2- I would link the link proposed by the video to be possible to be clicked
3- Some exposition imperfection (even if they make these video more "real and human")
4- Since quiz are not so difficult to be evaluated automatically I found it a bit annoying to notice them locked by not-purchsing, even if I understand there have to be something which would make the customer to purchase.
I've found the swirl experience great although a bit annoying sometimes but I've no clue on how to possibly improve it so.
Keep up with this great work!