Chevron Left
Retour à Exploration analytique de données

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

5,841 évaluations
846 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

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!

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.

Filtrer par :

801 - 816 sur 816 Avis pour Exploration analytique de données

par Joseph M K

31 janv. 2017

Clustering topic is covered superficially, too much time spend on employing ggplot graphs, not very useful since making graphs is straightforward on other software, like excel, once you aggregate datasets correctly. I had not found it very enriching as a course. I would merge this class within R-Programming section and call it Part 2 rather than categorizing into "Exploratory Data Analysis".

par Bartlomiej W

6 févr. 2016

Some parts of material is good quality, but some is bad - also some show bad practices in R. Extensively use swirl as assignments over self work. It is better to go through good tutorial over R base plotting system and ggplot2.

par David I

26 mars 2016

The final project did not require use of the material in the course beyond the first week and a half. I did not take any quizzes or otherwise have my knowledge tested on the material in the second half of the course.

par Rohith J

13 déc. 2016

Course content and assignments were difficult to follow. Loads of statistical content along with high-level R content means it was probably the toughest of the 4 I have taken so far in the Coursetrack.

par Dmitry R

6 févr. 2016

some swirl tests (4,5) don't work because of parameter method in qplot function. This parameter is not realy existed in this function now

par Freddie K

5 avr. 2017

Quite repetitious in covering basic graphing, and very shallow in regards of clustering, SVD and PCA.

par Tamaz L

5 avr. 2016

Very unprofessional, compared to other courses. It wasn't well organized.

par Desmond W

19 oct. 2016

About plotting in R. Not about generating real insights from EDA.

par Esther L

22 août 2019

Too weak regarding the clustering methods, very disappointed.

par ewa b

31 mai 2017

didnt get much useful-- a whole "course" on plotting? meh.

par Vineet P

2 juin 2020

Not upto expectations

par Michal K

10 mai 2016

too superficial

par Piyush V

21 juin 2016

Veyr boring

par Christy P

24 août 2017

How can you have a course on Graphic Devices and not show one screen shot of a graphic or open R to show how to perform the ideas around this topic?

par Nicholas

30 sept. 2016


par Carsten J

1 mars 2016

Material is to basic for an entire course.