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

4.7
4,992 notes
709 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

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!

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.

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226 - 250 sur 682 Examens pour Exploration analytique de données

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 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 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 xuanru s

Nov 28, 2016

GREAT TEACHING IN GRAPH, I LOVE THAT PART

par Saurabh G

Apr 14, 2017

nice

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 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 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

par Yang F (

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 George G A

Aug 20, 2017

Probably one of the most fun courses I have taken so far. It is an important step in every analysis.

par Sam M

Jul 09, 2018

Very good course!

par Luis M M R

Jan 21, 2018

very good.

Congratulations!

par 卢君

Apr 15, 2018

like this course

par Runhao Z

Oct 17, 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.

par Kyle H

Jan 17, 2018

Great course for plotting basics. Also really enjoyed the sections on SVD, PCA and Clustering.

par Bhargava B

Apr 02, 2018

This course really helps you to learn the fundamental exploration techniques. The assignments and the examples are really helpful.

par Fernando A F B

Jan 19, 2017

awesome!

par André V d C

Feb 02, 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.