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Comentários e feedback de alunos de Análise Exploratória de Dados da instituição Universidade Johns Hopkins

4.7
estrelas
6,012 classificações

Sobre o curso

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....

Melhores avaliações

CC

28 de jul de 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

23 de set de 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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776 — 800 de 851 Avaliações para o Análise Exploratória de Dados

por Divvya T

29 de out de 2017

good course

por Abhishek S

30 de mai de 2017

good course

por Ussama N

20 de mai de 2017

Good course

por 贝叶斯统计

23 de mai de 2016

还不错的R语言绘图入门

por Colin Q

1 de jun de 2017

very good!

por Jeremy O

9 de mar de 2017

excellent!

por Tim B

29 de dez de 2016

good intro

por mounika n

18 de set de 2022

its good

por Johnnery A

17 de nov de 2019

Excelente

por Khobindra N C

18 de mai de 2016

Excellent

por Rohit K S

20 de set de 2020

Nice!!

por Tae J Y

31 de mar de 2017

Good!

por Edward A S M

5 de dez de 2019

Good

por 木槿

2 de nov de 2018

good

por Anup K M

27 de set de 2018

good

por Isaac F V N

18 de abr de 2017

Nice

por Chan E

22 de mar de 2016

nice

por Adur P

28 de dez de 2017

A

por Saurabh K

27 de abr de 2017

G

por deepak r

2 de out de 2016

d

por Jose O

11 de fev de 2016

Insights delivered by the course were great. However, I think it emphasizes too much the lattice and basic plot systems to the point it is redundant with functionality on ggplot. It should focus more on concepts and techniques for delivering richer and meaningful graphics using ggplot rather than talking that much about technicalities on the basic plot and lattice systems.

Assignments were too basic and don't reflect all the concepts learned in the lessons e.g. clustering, which I think are of great interest for researchers.

por Ahmed M

24 de ago de 2016

The course is quite good and informative in the first two weeks covering a lot of information and a lot of exercises.

Week 3 is very unrelated and hard the videos and exercises are bad, and I had to do this part by myself again.

Also when we get to the final course project doesn't cover any of these techniques.

In my opinion, week 3 should be replaced with something more related to plotting systems and distributions, also one project would be enough.

por Andrew V

10 de jun de 2016

The course covers very limited subset of plots and mostly oriented to R-specific technical routines rather than overall approaches. Case-study example is helpful and contrary to the most comments I do appreciate the final course project: this how most problems are stated in real life. If you would like to cover more fundamental concepts behind exploratory analysis I would recommend other sources.

por Mohammad A A

11 de mar de 2019

It was a very useful course with some meaningful homework. My only criticism is that sometimes the theory and the practice are not well connected. Particularly the discussion of PCA, hierarchical clustering, k-means clustering and others. It would be benefit by providing more meaningful reading for those interesting in better connecting the two

por Arne S

31 de ago de 2019

did not like the swirl-tutorials. they were very tedious and sometimes labelled correct commands as false (e.g. when you typed = instead of <- for assigning a value to a variable)

also I was surprised that for a beginner programming course in R you had to apply specific functions such as grepl without the function being introduced in the course