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Learner Reviews & Feedback for Exploratory Data Analysis by Johns Hopkins University

4.7
stars
5,874 ratings
854 reviews

About the Course

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data....

Top reviews

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.

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776 - 800 of 824 Reviews for Exploratory Data Analysis

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 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.

By Fabiana G

Jun 23, 2016

Course feels somewhat abandoned by instructors. Content is okay, but can't help the feeling that it's basically a cash cow - students would benefit a lot if instructors were move involved.

By Ashish T

May 5, 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.

By Asier

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.

By 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.

By Andreas S J

Oct 4, 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.

By 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.

By ozan b

Feb 5, 2017

Course is good in general but "HIERACHICAL CLUSTERING" part is hard to understand and is not clear, should be explained more.

By 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.

By Katharine R

May 3, 2016

Good course, but the SWIRL exercises (and a few quiz questions) needed to be updated for the latest version of ggplot2.

By Johnny C

Mar 6, 2018

In general was good, but there were some lectures and exercises which were disorganized ("plots with colors")

By Erkan E

Jun 24, 2016

I wish there several comprehensive examples of exploring some real data as guided by the course instructors.

By Mehrdad P

Aug 25, 2019

The course was overall ok, but I wish discussions about k-means, PCA and SVD were divided into two courses.

By Daniel P

Dec 8, 2019

I've learned plotting in R. I expect to learn more in four weeks of "Data Science" specialization.

By Stuart A

Jul 18, 2020

Course hasn't been updated in a long time, some of the data needed for the projects has migrated.

By Francisco M R O

Jan 8, 2019

The third and fourth week were a big leap in knowledge and not really well explained, for me.

By sandeep d

Mar 10, 2018

Excercises are very good. But I believe lecture could be more interesting and easily taught.

By Guy P

Mar 26, 2016

It misses an assignment which will allow to practice the clustering skills.

By Alex s

Jan 17, 2018

It focus too much on the tools and a little bit on the analysis

By Amit O

Sep 30, 2017

faced many technical difficluties in pratcice exerices in swirl

By Eduardo V K

Jun 28, 2020

There seems to be some outdated info in several tests.