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

4.7
4,974 ratings
707 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

CC

Jul 29, 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 24, 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!

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1 - 25 of 679 Reviews for Exploratory Data Analysis

By Dale O J

Oct 16, 2018

This has been a challenging course for me, for whatever reasons. I have devoted a great deal of time in reading Dr. Peng's books as well as reviewing work product of other students to get a better grasp of the logic and methodology. I have enjoyed this course more than any of the preceding courses. And, the struggle I believe will be worth the effort and facilitate my completion of the data science specialization program.

By Faben W

Feb 04, 2019

This lesson could have been significantly improved if there was at least one assignment on clustering/dimensional reduction. Those are probably the hardest concepts thought thus far, so it would have been extremely useful to have at least one challenge to work through.

By JM

Jul 11, 2018

Once it got to the clustering section the lessons were inscrutable. Extremely difficult to understand and not explained well.

By Paul R

Mar 12, 2019

This course covers plotting (base, lattice, ggplot) then takes a confusing tour into heavy topics of clustering and dimension reduction, then flips back to coloring in charts. The order of the lectures is confusing and PCA/SVD needs more background, clearer explanation and treatment (gets covered a bit more later under regression). Assignments are good and swirl courses helped solidify the lectures.

By Rok B

May 15, 2019

This course is basically plotting with R and clustering/dimensionality reduction. There's is not enough emphasis on the later in my opinion. The final assignment focuses only on plotting, which is a shame.

By Dilyan D

Feb 12, 2018

This is the worst of the Data Science courses so far (they've all been pretty good up to this point).

It's called Exploratory Data Analysis, but is actually all about the graphics systems in R. And it does a botched job on those as well.

All quizzes and assignments are about the graphics systems. The only portion of the course that deviates from that is Week 3 (for which there is no quiz or project) where we "learn" about clustering and dimension reduction. However, that material is presented really poorly: not enough depth for someone who is already familiar with the subject matter; and not nearly well enough explained for newbies.

On the graphics side, none of the systems is explored in great depth. The lattice system is essentially just mentioned in passing.

To cap it all off, the brief for the last assignment is really ambiguous, which often causes perfectly valid work to be graded poorly by peers. (Just look at the forums, if you need proof.)

By Roman

Aug 30, 2018

Cons:

# Too much focus on hopelessly outdated R functions.

# Lectures are mostly powerpoint karaoke along the lines of "You can do that thing. And you can also do that other thing. And also you do this third thing" without much real-world application.

# ggplot2 is the only modern viz package that gets mentioned

Pros:

# The swirl exercises are great (but very buggy on Mac)

By Daniel H

May 13, 2019

Provides a solid overview of the base plotting system and a discussion (better elsewhere) of others. Introduces some higher level exploratory methods, without much information on either the theory or application (simply walks through the recipe). Assessments do not match the lecture material, so the credential is essentially meaningless. Read the associated book, watch the video lectures if you'd like. Don't bother with paying for the certificate.

By Sergey K

May 10, 2016

This course mostly about how to use plotting libraries in R.

By Luca R

Jun 10, 2017

The videos were merely repeating the content from swirl, with absolutely no added values.

By Beverly A

Sep 20, 2016

When it comes down to it, there's simply not the support to assist a student that has a really hard problem, "hacker mentality" seems to equate to "figure it out on your own cuz nobody's going to help you". If things do not work perfectly for you then you are likely never to be able to finish because your "peers" don't know any better either. The way this class is set up makes me angry every time I have to deal with it. I would probably be just as well served doing just the swirl() exercises. I would quit if I hadn't paid all the way through in advance. I can't believe this is the type of school John Hopkins is to produce a course of this quality, but I guess I have to.

By Jessica R

Dec 02, 2018

Very useful course

By Razib A K

Dec 18, 2018

good

By Yoselin A

Dec 19, 2018

Excellent course!

By 王昊辰

Dec 12, 2018

The data used for training are too big to be processed on my computer....

It is a real burden for my laptop when I use Rstudio to view some big files.....

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 Aman U

Jan 30, 2019

Fabulous

By James E H J

Jan 30, 2019

Great course to learn how to play with data - a good intro to things like Kmeans and hierarchical clustering, as well.

By Avizit C A

Jan 31, 2019

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

By Parker O

Feb 05, 2019

This has been very exciting!

By Qingchuan C

Nov 07, 2018

Some real stuff

By Anitha K

Nov 28, 2018

Excellent and thank you very much!

By MEKIE Y R K

Jan 16, 2019

really interesting

By Charbel L

Jan 19, 2019

Excellent course. Love the case studies

By Rodolfo R

Jan 09, 2019

great course