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

4.7
étoiles
5,066 évaluations
719 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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151 - 175 sur 691 Avis pour Exploration analytique de données

par Xray W

Feb 22, 2016

Pretty useful introduction to various plotting tools and some deep down insights as well.

par Isaac C B

Mar 12, 2018

Im really learning because of the exercises, they are very efficient!!

congratz coursera

par niki a

Mar 13, 2017

Nice course! Workload was just about right. clear lectures and well-designed projects.

par Gabriella J

Feb 26, 2017

Great course! It have been very useful for my job as data scientist! Thank u very much!

par ONG P S

Jan 16, 2020

As an auditor, this course taught me to see things more clearly from different angle.

par Сетдеков К Р

Jan 23, 2019

This is a great course on plotting data as well as finding underlying patterns in it.

par Nannette O S

Apr 16, 2018

Great course. The case studies are extremely helpful as well as the SWIRL exercises.

par Warwick T

Jun 15, 2017

Very enjoyable course although I think the workload could be more evenly distributed.

par Gioachino B

Jan 03, 2017

Excellent training! Lectures are easy to understand and let you focus on the subject.

par Avizit C A

Jan 31, 2019

A very good course describing commonly used graphical techniques with good examples.

par Jacques d P

Feb 04, 2018

Enjoyed this course. The course content and projects are very relevant to the field.

par Sean N

Feb 15, 2017

A nice introduction to operating on Data sets. Clear examples, interesting projects.

par Lluis G

Nov 28, 2016

Very good course that provides handy tools for data manipulation and representation

par Pratyush D

Feb 16, 2016

Very good course. Explains some very peculiar concepts of PCA and SVD very clearly.

par Shubham S

Oct 07, 2019

Thank you so much instructors, the learning curve till now has been great for me.

par Pooia L

Aug 31, 2018

I loved it, it improved my R skills in plotting and also gave me nice insights!!!

par Pradeep S

Jan 21, 2018

Very useful subject on churning data to derive meaningful and actionable insights

par Juliana C

Sep 25, 2017

Great course to learn how to build nice graphics and do exploratory data analysis

par Tai C M

Sep 23, 2017

This course is quite helpful. Especially the part which we learned to use ggplot.

par Admetos A

May 28, 2018

Found this course very impressive and challenging. Looking forward for the next.

par santiago R

Nov 14, 2017

Very nice course. good material. Not easy nor boring at all. Really learned here

par Ravi S R

Sep 11, 2017

This course is very important for beginners and it is also simple to understand.

par k.saikiran r

Jun 30, 2016

This course served as a great introduction to R and helped me to get ease with R

par danxu

May 22, 2016

Very useful !

Teacher is awesome, statement is clear and simple.

love this course!

par Raunak S

Oct 11, 2018

awesome course to learn exploratory data analysis using R programming language.