Learner Reviews & Feedback for Exploratory Data Analysis by Johns Hopkins University
About the Course
Top reviews
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.
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!
676 - 700 of 844 Reviews for Exploratory Data Analysis
By Jean-Philippe M
•Jun 15, 2019
More practical exercises using ggplot2 and clustering would be beneficial. Maybe need to be a 8 weeks module.
By Saurabh M
•Jul 30, 2017
Quantitatively assignments were less with no assignment for Week 3, however, the swirl exercises were good
By Anang S A
•Jul 15, 2019
this course is more about creating chart for EDA, need more material for reading/interpreting the charts
By Ankush K
•Jun 15, 2017
Useful for learning how to make plots, but not too detailed. Further analysis would have been helpful.
By Marcela Q
•Nov 26, 2019
Really good if you do not have any background in the field. But even if you do it is a great review
By Joe D
•May 19, 2019
Some of the links in the lectures are out of date, the forums usually have an updated link though.
By Lindy W
•Nov 24, 2016
Interesting learning more about ggplot and base plotting system, as well as clustering techniques.
By SUDIPTO M
•Oct 26, 2017
Thjis one of the best courses gives a great idea about plotting and exploratory data analysis !
By Kajal S
•Oct 3, 2019
Exploratory data analysis is a very important skill and it is a very good course to learn it.
By Eric J S
•May 29, 2019
Best of your courses yet. Doesn't suffer from difficulty spikes when you hit the projects.
By Gerardo M F G
•Nov 15, 2020
PCA and SVD are not included in any assignment, it will be great if they are in the future
By Huang-Hsiang C
•Jun 9, 2020
Plotting is very usefulIt would be great to have a step by step breakdown of PCA and SVD.
By Mark F
•Jul 5, 2017
SVD could be explained a little better i think. I am still not exactly sure how it works.
By Irmgard T
•Jul 23, 2017
great course...though I would have preferred less focus on cluster and k means analysis.
By Manuel M M
•Sep 27, 2019
It is a good course but in my opinion it is basically support with the R swirl() guide
By Ross D
•Sep 4, 2019
Was a little perplexed that we did not address clustering at all in the assignments.
By Prathamesh
•Jul 9, 2017
SVD & PCA videos need improvement in terms of background knowledge and understanding
By Migdonio G
•Apr 9, 2018
You should give more datasets for independent practice! Something we can play with.
By Sawyer W
•Aug 1, 2017
Good course. Mostly focuses on how to visualize statistics from the data quickly.
By Shuwen Y
•Jun 11, 2016
great course but wish to have more materials or explanation on svd and PCA part.
By KAMAL D
•Jun 1, 2021
Only the 3rd week was confusing but the confusion was revoked by swirl package
By Philip W
•Mar 21, 2017
Would have needed a litle more in depth explanation of the clustering analysis
By Subramanya N
•Dec 12, 2017
ggplot should have been given more emphasis. It warrants a course on its own!
By Greg R
•May 30, 2016
Pretty good course. Nice content. Middle section on clustering felt random.
By Pavel B
•Feb 18, 2016
I like the course and it was helpful in understanding how graphics work in R.
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