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

4.7
stars
6,088 ratings

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

CB

Dec 11, 2016

The course is interesting and the content is relevant. I do think that there are some issues with project 2 though. I did provide feedback on that to the course administrators.

LS

Nov 1, 2019

Good introduction. The swirl exercises kind of reproduce the lectures though- felt like it might not have been the most efficient use of time to go over the exact same example again.

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851 - 865 of 865 Reviews for Exploratory Data Analysis

By Bartek W

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Feb 7, 2016

Some parts of material is good quality, but some is bad - also some show bad practices in R. Extensively use swirl as assignments over self work. It is better to go through good tutorial over R base plotting system and ggplot2.

By David I

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Mar 27, 2016

The final project did not require use of the material in the course beyond the first week and a half. I did not take any quizzes or otherwise have my knowledge tested on the material in the second half of the course.

By Rohith J

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Dec 14, 2016

Course content and assignments were difficult to follow. Loads of statistical content along with high-level R content means it was probably the toughest of the 4 I have taken so far in the Coursetrack.

By Дмитрий Р

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Feb 7, 2016

some swirl tests (4,5) don't work because of parameter method in qplot function. This parameter is not realy existed in this function now

By Rahul R

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Jun 16, 2021

SVD should be better explained. I found diffucilut to understand. Some backgroeund matrices and it's operations should be explained.

By Freddie K

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Apr 5, 2017

Quite repetitious in covering basic graphing, and very shallow in regards of clustering, SVD and PCA.

By Tamaz L

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Apr 6, 2016

Very unprofessional, compared to other courses. It wasn't well organized.

By Desmond W

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Oct 20, 2016

About plotting in R. Not about generating real insights from EDA.

By Esther L

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Aug 22, 2019

Too weak regarding the clustering methods, very disappointed.

By ewa b

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Jun 1, 2017

didnt get much useful-- a whole "course" on plotting? meh.

By Vineet P

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Jun 2, 2020

Not upto expectations

By Michal K

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May 10, 2016

too superficial

By Piyush V

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Jun 21, 2016

Veyr boring

By Nicholas

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Oct 1, 2016

NEEEEEED TO EDIT MY PEER REVIEW FROM OTHERS

By Carsten J

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Mar 2, 2016

Material is to basic for an entire course.