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Avis et commentaires pour d'étudiants pour Exploration analytique de données par Université Johns-Hopkins

4.7
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5,605 évaluations
804 avis

À propos du cours

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....

Meilleurs avis

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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626 - 650 sur 777 Avis pour Exploration analytique de données

par Lindy W

Nov 24, 2016

Interesting learning more about ggplot and base plotting system, as well as clustering techniques.

par SUDIPTO M

Oct 26, 2017

Thjis one of the best courses gives a great idea about plotting and exploratory data analysis !

par kajal s

Oct 03, 2019

Exploratory data analysis is a very important skill and it is a very good course to learn it.

par Eric J S

May 29, 2019

Best of your courses yet. Doesn't suffer from difficulty spikes when you hit the projects.

par Huang-Hsiang C

Jun 09, 2020

Plotting is very usefulIt would be great to have a step by step breakdown of PCA and SVD.

par Mark F

Jul 05, 2017

SVD could be explained a little better i think. I am still not exactly sure how it works.

par Irmgard T

Jul 23, 2017

great course...though I would have preferred less focus on cluster and k means analysis.

par Manuel M M

Sep 27, 2019

It is a good course but in my opinion it is basically support with the R swirl() guide

par Ross D

Sep 04, 2019

Was a little perplexed that we did not address clustering at all in the assignments.

par Prathamesh N

Jul 09, 2017

SVD & PCA videos need improvement in terms of background knowledge and understanding

par Migdonio G

Apr 10, 2018

You should give more datasets for independent practice! Something we can play with.

par Sawyer W

Aug 02, 2017

Good course. Mostly focuses on how to visualize statistics from the data quickly.

par Shuwen Y

Jun 11, 2016

great course but wish to have more materials or explanation on svd and PCA part.

par Philip E W J

Mar 21, 2017

Would have needed a litle more in depth explanation of the clustering analysis

par Subramanya N

Dec 12, 2017

ggplot should have been given more emphasis. It warrants a course on its own!

par Greg R

May 31, 2016

Pretty good course. Nice content. Middle section on clustering felt random.

par Pavel B

Feb 18, 2016

I like the course and it was helpful in understanding how graphics work in R.

par RobinGeurts

Feb 21, 2019

End assignement was relatively easy compared to the examples in the lectures

par Mario S P G

Sep 17, 2018

Good beginners course with helpful tools to take a first glance to your data

par Polina

Apr 25, 2018

Nice course, very useful. I wish the links were updated more often, however.

par Gao Q

Jul 23, 2018

Great content for beginners to get familiar with various graphic tools in R

par Mario P

Jan 20, 2018

I suggest to shift a little more the focus on svd and clustering techniques

par Olga H

Sep 22, 2017

Good course, would have likes more practice & testing on the clustering stu

par Andrew W

Mar 19, 2018

Challenging but great fun and really helped me to get more familiar with R

par Carlos L

Jun 22, 2016

swirl is very used in this course. It is one of the best tools to learn R