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.
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!
par 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.
par 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.
par 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.
par 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.
par 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.
Aug 30, 2018
# Too much focus on hopelessly outdated R functions.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
# The swirl exercises are great (but very buggy on Mac)
Jul 11, 2018
Once it got to the clustering section the lessons were inscrutable. Extremely difficult to understand and not explained well.
par 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.)
par Luca R•
Jun 10, 2017
The videos were merely repeating the content from swirl, with absolutely no added values.
par 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.
par Sergey K•
May 10, 2016
This course mostly about how to use plotting libraries in R.
par Anang S A•
Jul 16, 2019
this course is more about creating chart for EDA, need more material for reading/interpreting the charts
par Alex B•
Jul 13, 2019
This series has been life changing for me. Thank you.
par José S C S•
Jul 07, 2019
This course teaches how to use three different plotting systems in R. Given the dominance of the tidyverse/ggplot2 paradigm, I really appreciate the opportunity to learn the base plotting system and the lattice plot system.
par Elimane N•
Jul 03, 2019
That's a great and very usefull course!
par Marta R•
Jun 28, 2019
Really good course, with amazing videos and examples. I have learned a lot and I think the projects were really interesting.
par Maria A P d S•
Jun 24, 2019
par Amy B P•
Jun 18, 2019
Very well formed course. Enjoyed the course and projects.
par Diego A Q•
Jun 18, 2019
Great course, it teaches you a lot about how to create plots, charts and other tools using R code. This course is focused on "get to know your data" by using all this tools during a research process. It is like the previous step you have to do before going into any analytics.
par Jean-Philippe M•
Jun 16, 2019
More practical exercises using ggplot2 and clustering would be beneficial. Maybe need to be a 8 weeks module.
par William B B•
Jun 12, 2019
Excellent course and applicable in my work right now
par Santi M•
Jun 12, 2019
par Jamie R•
Jun 07, 2019
Just an extended course on using R. There was little strategies for Exploratory Data Analysis, infact the example jumped from a high level view of the data to then start looking at individual counties. There are multiple tools in the market that will deliver in a better and faster way for exploratory data analysis. This course should be more targeted at developing a skill set that is tool agnostic.
par Eric J S•
May 29, 2019
Best of your courses yet. Doesn't suffer from difficulty spikes when you hit the projects.
par Jorge B S•
May 28, 2019
Very useful course with interesting contents.