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Avis et commentaires pour l'étudiant pour Exploration analytique de données par Université Johns-Hopkins

4,950 notes
704 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


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!

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276 - 300 sur 676 Examens pour Exploration analytique de données

par Mohammad S

Jul 26, 2017

Awesome !!!

par Eliomar F

Feb 26, 2018

Excelente curso.

par Choo E

Jul 17, 2017

I really appreciate this course.

par Massimo M

Aug 28, 2017

Great course, very useful exercise and case study.

par Isaac C B

Mar 12, 2018

Im really learning because of the exercises, they are very efficient!!

congratz coursera

par Mohammad A

Jul 04, 2018

Excellent explanation and adding very good skills on the way of data science specialization.For some slides they should be updated to have working URLs , some seems old and absolute now

par Melanie B

Mar 15, 2018

The case studies were so helpful.

par Saravanan

Mar 02, 2017

useful course for me . thanks to my tutor

par Karan B

Mar 04, 2018

Excellent course

Swirl lesson makes learning data science much easier

par reem z

Jun 23, 2018

A great course I had to do research on the side to get some ideas and concepts that were presented in this course.... if this was my first course i would have found that not a good thing . However, every time i search i get better as a data science student and i know what to search for and how to find it and i think this is essential if you want to be a data scientist :)

par Wayne H

Mar 03, 2017

Good introduction to graphics systems and principles. Practical exercises are well conceived.

par 刘博

Feb 03, 2017

good course!

par Samir A G

Oct 23, 2016

Thank you very much, it was very interesting !!

par xuanru s

Nov 28, 2016


par Ravi K

Nov 04, 2016

Excellent course but would have helped better if there would have been assignment related to clustering.

par Saurabh G

Apr 14, 2017


par Amanuel G

Jan 06, 2017

It was a wonderful experience to read the structure of data before delving into the advanced statistical levels of data analysis.The need for inclusion or exclusion of dependent variables or dimension reduction in regression analysis can be intuitively understood and visualized using Data Exploratory techniques and then we have the clue as what to do in the next level.It is like putting the whole characteristic of the data under full control.

par Pradeep S

Jan 21, 2018

Very useful subject on churning data to derive meaningful and actionable insights

par James A

Nov 28, 2016

Very excellent course structure. Gives you all the bases you need to get you started in exploring your data.

par Balinda S

Dec 11, 2016


par Stefan P L

Feb 09, 2018

Overall good course! Though I hope there is more exercise in SVD/PCA part

par Tan S L

May 10, 2017

Useful course but it is quite intense

par Avinash A

Aug 30, 2017

Nice content. Make sure to take the SWIRL course offered. That really helps to get a hold on the course. Recommended!

par Sumeet M

Nov 06, 2017

Good Course

par Damjan S

Jun 10, 2017

This was the course that I've enjoyed it the most. Especially the data visualization part