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

5,946 ratings
871 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

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!

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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176 - 200 of 840 Reviews for Exploratory Data Analysis

By Alberto G

Sep 12, 2018

Very interesting and useful for its applicability to a lot of different professional areas.

By Ricardo R

Oct 24, 2016

Excelent course! Very direct and informative, leaving many doors open to individual quests.

By Ghazouan S

Oct 2, 2016

I love all those courses, I have learned so much and I'm planning to complete all 10 units.

By Pratama A A

Jul 24, 2020

I encourage to read the book ,and learn the unsupervised machine learning algortihm better

By Thiago M

Aug 12, 2019

Course material and projects help a lot in learning and improving data analysis techniques

By Gat T

Jan 27, 2019

I really liked this course. I felt like a learnt a lot especially with all of the projects

By Damian

Jun 10, 2017

This was the course that I've enjoyed it the most. Especially the data visualization part


Apr 22, 2021

Great course with important lessons. Thanks for the lessons and the information provided.

By Anusha V

May 30, 2017

Amazing course. challenging and you learn a LOT (particularly about graphics tools in R).

By Nishchal S

May 17, 2016

Some functions are so tough to remember but general ideas that i received is wonder full.

By Ray W

Feb 22, 2016

Pretty useful introduction to various plotting tools and some deep down insights as well.

By Isaac C

Mar 12, 2018

Im really learning because of the exercises, they are very efficient!!

congratz coursera

By niki a

Mar 13, 2017

Nice course! Workload was just about right. clear lectures and well-designed projects.

By Gabriella J

Feb 26, 2017

Great course! It have been very useful for my job as data scientist! Thank u very much!

By Andrés D C

May 27, 2021

This is essential for every posterior course, take care of understanding the concepts.


Jan 15, 2020

As an auditor, this course taught me to see things more clearly from different angle.

By Сетдеков К Р

Jan 23, 2019

This is a great course on plotting data as well as finding underlying patterns in it.

By Nannette S

Apr 16, 2018

Great course. The case studies are extremely helpful as well as the SWIRL exercises.

By Warwick T

Jun 15, 2017

Very enjoyable course although I think the workload could be more evenly distributed.

By Gioachino B

Jan 2, 2017

Excellent training! Lectures are easy to understand and let you focus on the subject.

By Avizit C A

Jan 30, 2019

A very good course describing commonly used graphical techniques with good examples.

By Jacques d P

Feb 4, 2018

Enjoyed this course. The course content and projects are very relevant to the field.

By Sean N

Feb 14, 2017

A nice introduction to operating on Data sets. Clear examples, interesting projects.

By Lluís G

Nov 28, 2016

Very good course that provides handy tools for data manipulation and representation

By Pratyush D

Feb 16, 2016

Very good course. Explains some very peculiar concepts of PCA and SVD very clearly.