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!
676 — 700 de 844 Avaliações para o Análise Exploratória de Dados
por Jean-Philippe M
•15 de jun de 2019
More practical exercises using ggplot2 and clustering would be beneficial. Maybe need to be a 8 weeks module.
por Saurabh M
•30 de jul de 2017
Quantitatively assignments were less with no assignment for Week 3, however, the swirl exercises were good
por Anang S A
•15 de jul de 2019
this course is more about creating chart for EDA, need more material for reading/interpreting the charts
por Ankush K
•15 de jun de 2017
Useful for learning how to make plots, but not too detailed. Further analysis would have been helpful.
por Marcela Q
•26 de nov de 2019
Really good if you do not have any background in the field. But even if you do it is a great review
por Joe D
•19 de mai de 2019
Some of the links in the lectures are out of date, the forums usually have an updated link though.
por Lindy W
•24 de nov de 2016
Interesting learning more about ggplot and base plotting system, as well as clustering techniques.
por SUDIPTO M
•26 de out de 2017
Thjis one of the best courses gives a great idea about plotting and exploratory data analysis !
por Kajal S
•3 de out de 2019
Exploratory data analysis is a very important skill and it is a very good course to learn it.
por Eric J S
•29 de mai de 2019
Best of your courses yet. Doesn't suffer from difficulty spikes when you hit the projects.
por Gerardo M F G
•15 de nov de 2020
PCA and SVD are not included in any assignment, it will be great if they are in the future
por Huang-Hsiang C
•9 de jun de 2020
Plotting is very usefulIt would be great to have a step by step breakdown of PCA and SVD.
por Mark F
•5 de jul de 2017
SVD could be explained a little better i think. I am still not exactly sure how it works.
por Irmgard T
•23 de jul de 2017
great course...though I would have preferred less focus on cluster and k means analysis.
por Manuel M M
•27 de set de 2019
It is a good course but in my opinion it is basically support with the R swirl() guide
por Ross D
•4 de set de 2019
Was a little perplexed that we did not address clustering at all in the assignments.
por Prathamesh
•9 de jul de 2017
SVD & PCA videos need improvement in terms of background knowledge and understanding
por Migdonio G
•9 de abr de 2018
You should give more datasets for independent practice! Something we can play with.
por Sawyer W
•1 de ago de 2017
Good course. Mostly focuses on how to visualize statistics from the data quickly.
por Shuwen Y
•11 de jun de 2016
great course but wish to have more materials or explanation on svd and PCA part.
por KAMAL D
•1 de jun de 2021
Only the 3rd week was confusing but the confusion was revoked by swirl package
por Philip W
•21 de mar de 2017
Would have needed a litle more in depth explanation of the clustering analysis
por Subramanya N
•12 de dez de 2017
ggplot should have been given more emphasis. It warrants a course on its own!
por Greg R
•30 de mai de 2016
Pretty good course. Nice content. Middle section on clustering felt random.
por Pavel B
•18 de fev de 2016
I like the course and it was helpful in understanding how graphics work in R.
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