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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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5,877 évaluations
855 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
23 sept. 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
28 juil. 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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576 - 600 sur 824 Avis pour Exploration analytique de données

par Xiao W

27 oct. 2016

Thanks

par Medha B

9 oct. 2020

Great

par Robert J C

25 juil. 2019

Good.

par Adán H

5 oct. 2017

Good!

par Rafael L G

6 juin 2017

great

par zhao m

1 nov. 2016

good.

par Marco A P N

1 juin 2016

Great

par Yusuf S

19 mai 2016

great

par Sameeksha S

12 mai 2021

good

par Souvik P

5 août 2020

good

par Pitak P

4 oct. 2019

Good

par Razib A K

18 déc. 2018

good

par Ganapathi N K

30 avr. 2018

Nice

par Jay B

15 août 2017

good

par Saurabh G

13 avr. 2017

nice

par Larry G

7 févr. 2017

Nice

par 刘治

17 juil. 2016

good

par Prakash M S G C

24 mai 2016

Good

par 朱荣荣

9 mars 2016

good

par 丁雪松

15 juin 2020

💯

par Amit K R

21 nov. 2017

ok

par Ganesh P

28 nov. 2017

V

par Wei W

11 sept. 2017

C

par Balinda S

11 déc. 2016

T

par Phillip K

20 mars 2018

Good stuff just as I have come to expect from this University and the courses that are part of this Signature Track.

A great deal of the lectures and work on assignments/quizzes/projects was learning and using the various plotting systems in R. Certainly this is important, but to put it into perspective, I spent four hours creating six plots for the final project, when I was able to use Tableau Desktop to create all six plots in under five minutes.

So formally learning the data exploration techniques was good, but expect much of this course to be about learning the R plotting systems.

That said, there is a point in this course (and the first time for all the courses to this point) where the topic suddenly got very, very technical. When clustering techniques were introduced it felt as if you were turned on your head as the focus suddenly went from various ways of plotting data in R to being neck deep in the explanation of clustering techniques that require a great degree of Linear Algebra knowledge.

Don't panic though. While there are questions in the guided assignments that are difficult, you don't really need to recall all of your Linear Algebra courses from college to pass this course. After all, R "has a package for that."