Comentários e feedback de alunos de Análise Exploratória de Dados da instituição Universidade Johns Hopkins
Sobre o curso
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!
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
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