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

4,889 notes
696 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


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!


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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576 - 600 sur 668 Examens pour Exploration analytique de données

par Liang Y

Oct 28, 2016

Like the clustering

par Jeff B

Mar 04, 2018

The plotting aspects of this course appealed to my visual sense.

par Adur P

Dec 28, 2017


par Freddy M C F

Jun 30, 2017

Very good Introductory Course. Thank you!

par Guilherme B D J

Jun 09, 2016

The only missing point I would say about this course is how to deal with skew data and/or outliers. Although it is not specific to "cleaning data", I think there is a good opportunity there to at least give some hints on this subject

par Ankush K

Jun 15, 2017

Useful for learning how to make plots, but not too detailed. Further analysis would have been helpful.

par Carlos R

May 29, 2017

I love the course. However, the treatment of PCA, SVD, and colors seems to me very long and slow. Maybe a more direct and quick overview would be better. Even with that expection I really enjoy the course.

par Shuwen Y

Jun 11, 2016

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

par jishuenkam

Aug 27, 2016

Hopefully it could be clearer on dimension reduction.

par Ankit A

Dec 16, 2016

The exploratory part was very good. But, PCA was a waste of time.

par Christian B

Dec 11, 2016

The course is interesting and the content is relevant. I do think that there are some issues with project 2 though. I did provide feedback on that to the course administrators.

par Kai C Y

May 25, 2016

More real data example is even better!!!

par Murugesan A

Mar 23, 2017

Well crafted, carefully designed learning materials!

par kathy k

Dec 11, 2016

good overview of how to make graphs!

par Khobindra N C

May 18, 2016


par Christopher L

Jul 24, 2017

great intro to the plotting system. could be better with a dimension reduction assignment or quiz. this is very important!

par Mohammad F H

Sep 15, 2016

Very detailed. Like the case study by Dr. Peng.

par Igor T

Jan 30, 2017

Good introduction to patterns recognition. I found principal components analysis technique very useful. It would be great to provide more lectures about this topic.

par Andrew W

Mar 19, 2018

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

par Richard D

Jun 12, 2017

Great overview, especially the parts on dimension reduction.

par Anirban C

Jul 19, 2017

Nice course! Assignments could have been a little more challenging

par Sabawoon S

Jul 04, 2017

Very helpful

par Greg A

Feb 22, 2018

This is a very good course, at times it felt like the instruction was to do things mechanically without understanding the motivation. Perhaps this should come after or in conjunction with Statistical Inference

par Connor G

Aug 14, 2017

I enjoyed the course and learned important graphing concepts for R/RStudio. I just wish the assessments had been a little more rigorous, as it felt like I could have done better but still passed the projects anyway.


Oct 26, 2017

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