CC
2016年7月28日
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.
Y
2017年9月23日
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!
創建者 Ashish T
•2018年5月5日
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.
創建者 Asier
•2016年3月10日
The course content applies to R. The teachers focused on the programming language rather than the application of the existing graphs to explore data.
創建者 Gianluca M
•2016年10月13日
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.
創建者 Andreas S J
•2017年10月4日
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.
創建者 Dylan P
•2018年5月13日
I would have liked an assignment to focus on the clustering methods and I think dimension reduction was reviewed way too quick.
創建者 ozan b
•2017年2月5日
Course is good in general but "HIERACHICAL CLUSTERING" part is hard to understand and is not clear, should be explained more.
創建者 Casey B
•2016年5月12日
Good class - links and slides have not been updated recently. Frustrating to finish without the exact linkts to the data.
創建者 Katharine R
•2016年5月3日
Good course, but the SWIRL exercises (and a few quiz questions) needed to be updated for the latest version of ggplot2.
創建者 Johnny C
•2018年3月6日
In general was good, but there were some lectures and exercises which were disorganized ("plots with colors")
創建者 Erkan E
•2016年6月24日
I wish there several comprehensive examples of exploring some real data as guided by the course instructors.
創建者 Mehrdad P
•2019年8月25日
The course was overall ok, but I wish discussions about k-means, PCA and SVD were divided into two courses.
創建者 Daniel P
•2019年12月8日
I've learned plotting in R. I expect to learn more in four weeks of "Data Science" specialization.
創建者 Stuart A
•2020年7月18日
Course hasn't been updated in a long time, some of the data needed for the projects has migrated.
創建者 Francisco M R O
•2019年1月8日
The third and fourth week were a big leap in knowledge and not really well explained, for me.
創建者 sandeep d
•2018年3月10日
Excercises are very good. But I believe lecture could be more interesting and easily taught.
創建者 Guy P
•2016年3月26日
It misses an assignment which will allow to practice the clustering skills.
創建者 Alex s
•2018年1月17日
It focus too much on the tools and a little bit on the analysis
創建者 Amit O
•2017年9月30日
faced many technical difficluties in pratcice exerices in swirl
創建者 Victor M C T
•2022年1月4日
The swirl labs failed, I never could load the "field" module.
創建者 Eduardo V K
•2020年6月28日
There seems to be some outdated info in several tests.
創建者 Rafael A
•2017年3月23日
First two weeks are too repetitive with other courses
創建者 Kevin F
•2020年7月15日
pretty brief and basic. no assessment on clustering.
創建者 Erwin V
•2016年3月12日
Interesting stuff, but not a lot of detail
創建者 Oscar P G P
•2020年9月17日
It's necessary for more examples!!!!
創建者 Lidiya N
•2019年4月28日
Absolutely No technical help, like insane amounts of homework for each week. People have jobs and businesses to run. Incredibly short duration. Like literally this should have been spread out several more weeks. I would have dropped the class but I can’t. It’s so difficult to get i to the first set of practice assignments and these several sets. Honestly, I am literally getting no help on it and probably won’t pass because I am missing the deadline. I finished 5 coursera courses working on them for 24 none stop. I’ve literally been at this class all day. Besides all the insane amounts of assignments there’s tons of videos to watch and uploads to do. Go buy some books or take another class unless you are unemployed or have nothing better to do.