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

4.7
4,939 notes
703 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

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.

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!

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101 - 125 sur 675 Examens pour Exploration analytique de données

par Jhon A M L

Oct 19, 2016

Great!!

par Ted M

Oct 05, 2016

The lectures in this course included theory and examples on PCA and SVD - however this was missing from the practical materials

par Arindam M

Jan 06, 2017

A great course. I was hoping to get some more hands on the actual case study though. It was mentioned that Exploratory Analysis is some times intertwined with modeling - and I think in later course it might get covered. But just a glimpse of the relation in the case study would have been helpful.

par Meng Q

Aug 23, 2016

Well designed!

par Emily

Nov 20, 2017

very good course

par Robert K

Jun 12, 2017

Very useful!

par Erdem Y

Jun 13, 2017

There should be more content devoted to SVD . more theory and quiz questions and workouts to emphasize the methodology.

par hyunwoo j

Mar 16, 2016

very very useful

par Jerry V

Nov 17, 2016

An interesting course

par Shams M S

Feb 28, 2017

Great Projects!

par Christian

May 08, 2017

Loved the course!

par Allister G A

Oct 30, 2017

Informative and really fun to do.

par Nitika S

Jul 11, 2017

Very good material and structure of course! Thanks a lot.

par Ishwar N

Feb 18, 2018

Highly recommended course for budding data scientist. I loved the John Hopkins univ pedagogy and peer review system. The content is great.

par Yergali B

Mar 16, 2016

I strongly suggest for future Data scientist, if you know R language with making Plots, you can be a good analytic

par Jean P L

Feb 03, 2017

I love these courses

par GAURAV S

Aug 08, 2016

Nice course

par Anna B R

Oct 24, 2017

Great course

par Sanjeev K

Mar 14, 2018

Great Insights to graphs, plots . histograms

par antonio q

Dec 30, 2017

very good course, a fast and robust was to learn data analysis using R, thanks

par TARUN S

Apr 29, 2017

I really appreciate the course design. Even if somebody doesn't have much background in R, she/he can comfortably learn from the videos and understand the concepts. The exercises and project assignments are challenging and actually help you practice and re-visit the lectures and explore further. Though I had already known and used Clustering, PCA and SVD in my work before, I really liked the way these concepts were explained here. I would strongly recommend this course to anybody who is keen to see R in action!

par Laura B

Jul 07, 2017

Good info. But I would like to have reminder emails for the due dates.

par Zhao M

Nov 01, 2016

good.

par Michael R

Jan 08, 2016

ggplot2 module was extremely helpful

par Diana S

Feb 11, 2016

Thank you son much!!!!

I really like the course.

It help me in my job =)