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

Excellent course. I learned more than I expected. A technique that was always at hand but never used: perform analysis through graphics exploring countless variables at a single time.

This was incredibly useful because it gives you a feel for the datasets and tools with which to explore them. I really wasn't aware of the base and lattice plotting systems until now.

Amazing! Learing so much how to explore the data for the first time. This is a must do for anyone who wants to be a data scientist. Now I can use ggplot without any trouble. Thanks!

Me encantó el curso, fue muy fluido con muy buenos ejemplos y las actividades prácticas fueron realmente un aporte y un desafío para complementar los contenidos entregados

This is a great introductory course on the topic and on R language.

You will get acquainted with basic R functions which are most useful for initial statistical analysis.

One of the most fulfilling courses I've taken. Already used what I've learned to analyse the COVID 19 data and get more information from it, learning at the same time.

Week 3 - clustering concepts appear hard to comprehend initially. This week should first start with a practical example/use of clustering and then move on to technical

Its one of the most important steps in learning data science. Before even jumping into the real thing, it is worthwhile to explore a little bit the data set at hand.

For someone new to data analytics, this was another great, rewarding course. But as with the others, it demands exploration beyond the lectures and course materials.

Prof. Peng teaches you not only how to use the r base plotting system but also how to make wonderful graphs using the lattice and ggplot2 packages. Awesome course!

Very good resume of the previous lessons, you lear plotting, charts, working with big matrices, create a good practical workflow to understand your first analyses

Material teached in this course is must have for everybody who wants to use R for Data Science. Exploratory Data Analysis is one of first steps in every project.

Great course, an excellent instructor who makes the videos easy to watch and listen.

Assignments were very important to me, as I learned a lot while doing it.

I learned a lot, this course more than others, really expanded my competence and appreciate for the capabilities of R, especially is visualization toolbox.

Great course. Really does a good job of describing the goal of EDA and getting people excited about what questions you might be able to answer with data.

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.....

pretty good starter course. I liked 40 min Case Study video at the end. It was very helpful to watch the instructor do the analysis from start to finish.

Excellent course!

Congratulations and thanks to the teachers of this course for sharing their knowledge on such an engaging subject that is Data Science.

I think this is a great course. I learned a lot about data plotting and some multivariate techniques for understanding underlaying patterns of the data.

Wonderful course with lot of graphical representation of the data. Dimensional reduction and Clustering analysis needs a bit more detailed explanation.

Very solid class in terms of R's base plotting system. I wish Coursera offered an advanced class focusing on ggplot2 and the wider world of dat viz.

This was a great course. I learned how to use several graphic systems within R, and to imagine how to make clear answers to questions using plots.

Very good class. Of the four I've taken so far, this one has given me the most confidence that I could be successful as a data scientist/analyst.

This was an important class because in future classes in the certification peer reviewed projects require some sort of exploratory data analysis.

Great Course. Lectures did diverge from Quizes and projects but still was good practice of looking at a set of data and reporting out from it.