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

4.7
stars
6,051 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

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.

YF

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!

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51 - 75 of 856 Reviews for Exploratory Data Analysis

By Tad S

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Feb 1, 2016

If you know some R programming and want to learn how to generate plots for your data analysis, this course will give you a good start. I highly suggest doing swirl exercises after watching the lecture videos to reinforce your understanding of the course materials.

By Nikolai A

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Oct 3, 2017

I had a lot of experience with graphing data before this class in Mathematica and Excell, however, graphing in R seems so much easier and a lot more fun. This class did a great job of explaining the process, and the assignments felt more like games than homework.

By Keith H

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Jun 9, 2020

Very much enjoyed the discussions about how to initially analyze data before leaping into modeling. I feel I need to continue to look at PCA and SVD and understand them better. They seem very helpful but I feel like I still don't fully grok how to use them.

By Hesham S S E

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Jul 29, 2020

This course is really essential for any beginner in the field of data analysis as it is not only wokring with the tools, but also it gives you the mechanism of tackling the problems with the right technique of thinking and formulating the right questions.

By John R T

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Jun 8, 2020

Genuinely enjoyed this course. Will be practicing and using what I learned for some time!😊😊😊

If there were anything I would add to the course is maybe a short lecture on how to create 3-Dimensional graphs.

Regards, JT -- See you in the next class!

By Sajal J

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Aug 12, 2020

Very good course. I found hierarchical clustering to be very simple and yet so useful. Assignments are also very good because they are based on real data which is often messy and we have to clean and identify keywords/patterns for our analysis.

By Rodney J

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Jun 16, 2017

Great course. This course required us to create multiple plots using different R libraries created for the purpose. Although ggplot2 seems to be very popular, the base plot system and the lattice plot system provide compelling alternatives.

By Adi T

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Jan 21, 2017

It starts to get a little more technical and complicated when I reach Week 3. A lot of things about Dimension Reduction and K-means method. I would love to have some assignments or exercises on that.

Other than that, I love this module.

By Dev P

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Jan 5, 2020

Great course providing a good overview into the various plotting systems in R. I enjoyed the introduction to principal components analysis and singular value decomposition, but could have used more material to practise these methods

By John B

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Sep 22, 2018

The exploratory data analysis is a very important part of the elaboration of a data product because this period helps to understand the most important variables and the elements to construct models and visualize an early result.

By Omar

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Dec 14, 2016

One of the best parts is the introduction of Singular Value Decomposition and Principal Component Analysis. Also does K-means and other clustering.

I would recommend reading the handouts to you get the math behind the technique.

By Rosa C V

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Feb 3, 2020

Me encanto el curso! Buenos profesores, el curso estuvo modulado de la manera interesante y el ingles estuvo fácil de entender. La parte practica me motivo a poder continuar con los siguientes cursos de la especialización.

By Lloyd N

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Dec 20, 2016

This course is excellent in that it gave a great introduction to the plotting functions in R. They also introduced singular value decomposition, which is a concept that is interested but wish the course went deeper into.

By BOUZENNOUNE Z E

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Mar 10, 2018

That's a wonderful course, especially if you take it with the specialization, and also better if used with the recommended books. I highly recommend, but once you finish it, you should continue to work on your own ;)

By Garrett F

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May 22, 2020

Learned how to look at data and get some first impressions using exploratory data analysis techniques. I wish the second course project was more involved by including hierarchical clustering methods in the analysis.

By Varun B

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Mar 22, 2018

The right amount of theory and practical. This course will take you through the process on how do you ascertain what's important? and how to find that needle in the haystack? . Absolutely recommend to take this up.

By Runhao Z

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Oct 16, 2017

The peer review takes so long..................................................................................... which costs me extra money even though I have finished all the stuff 1.5days before the last day.

By Rouholamin R

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Feb 16, 2019

I learned a lot from this course. Content which the course covers was a third of what I learnt from this course. the best thing about it is learning the pattern of thinking about exploring a whole new dataset.

By James W

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Sep 7, 2016

Really nicely explained, learned so many useful methods for data analysis in R. The dimensionr reduction and principal component analyses walkthroughs were a little tricky for a newbie in those areas though.

By Juan P L R

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Sep 6, 2020

Excellent course for Exploratory Data Analysis. The focus on plots with the three systems R handles was great. The lecture are great overall, along with the assignments. It is really an enjoyable course.

By Yang F

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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!

By Craig

•

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.

By Felix E

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Jul 29, 2019

Good Course. Would've like a bit more about more advanced plotting and less about clustering techniques but that is probably mainly down to what data each is intending on handling after this course.

By André V d C

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Feb 1, 2016

Muito bom o curso com abordagem das formas de exploração dos dados via gráficos. Não achei um curso pesado e denso mas substancial para o aprimoramento na linguagem R e na ciência de dados.

By Luis T

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Jul 17, 2022

The content of this course is enough to create a great exploratory data analysis. It teaches some interesting tools and techniques to analyze data. Clustering section was my favorite part.