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

4.7
estrelas
5,972 classificações
874 avaliações

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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651 — 675 de 843 Avaliações para o Análise Exploratória de Dados

por Hernan S

6 de mar de 2018

I learned a lot on this course, it helped me to understand and identify some of the situations I experience at work. Totally recommended if you want to apply it right away.

por Terry L J

18 de out de 2018

Seems this would type of course in an online learning MOOC would be better if it was more direct hands on "how to" and less focused on explanatory fluff (academic style) .

por Igor T

30 de jan de 2017

Good introduction to patterns recognition. I found principal components analysis technique very useful. It would be great to provide more lectures about this topic.

por Carlos G W

6 de set de 2020

I enjoyed the course and learned a good deal. However, the level of challenge of the projects is much higher than the scant explanation provided by Dr. Peng.

por DESIREE P

19 de abr de 2021

We learn very useful things. However, there is little emphasis on the statistical part (singular value decomposition) which I think deserved more exercises.

por Diego T B

17 de nov de 2017

Interesting. But I would prefer the differences between comparison plots. What do they are useful and why is it better to plot with bars rather than lines.

por Robert W S

14 de fev de 2016

A quiz or project question on k-means clustering or PCA would be nice. Overall the course provided solid coverage of the three main plotting systems in R.

por Guillaume S

8 de jun de 2018

Interesting course to know plotting systems and to have a first view on clustering and dimensions reduction. This part should be however more developed !

por Hyun J K

17 de abr de 2018

Great lecture. I hope there were more assignments. (1 per a week maybe).

I learned many statistical concepts and rcodes by taking this course.

Thank you:)

por Hank C

13 de set de 2020

Course material, lectures, exercises are excellent.

There was not enough theory, and there was too much specific to R and graphing packages covered.

por Robin S

28 de fev de 2017

The course was fantastic. It was very challenging. I could do with some additional opportunities for exploratory analysis to reinforce some concepts.

por Steven C

15 de mar de 2017

Good course on plotting libraries and useful plots in R. Wished there was more coverage of ggplot and less on lattice, but overall a useful course.

por Ramakumar A

3 de jul de 2020

though presentation was good ,felt it should have been better in small sessions , lost interest half way through , continued later to complete

por Ashutosh K S

7 de fev de 2017

It delves into many important topics. I would advice to explore the topics in much more depth on your own. Overall a good breadth of topics.

por Bijan S

30 de jan de 2016

The course is useful with a lot of learning.

The second half needs more of improvement, I think the pace is quite fast compared to others.

por Piyush D

15 de mai de 2019

Awesome course ! It reaches you the crux of exploration of data . Although the SVD section could have been more thorough and detailed.

por Marc T

31 de mar de 2019

Great introduction! I am eagerly awaiting the opportunity to apply clustering and dimension reduction on real data in future courses.

por Andres U

21 de fev de 2017

Really helpful. I really enjoyed getting familiar with plotting systems and also increasing my abilities dealing with data frames

por Tony W

21 de jun de 2016

Very interesting and insightful course. I enjoyed it.

Assignment was okay, could have provided more challenge and depth though.

por Nils M

27 de out de 2016

Very good course. I liked the clustering examples. They were a little bit detached from the rest, but they were also great.

por Christopher L

23 de jul de 2017

great intro to the plotting system. could be better with a dimension reduction assignment or quiz. this is very important!

por Luiz E B J

3 de out de 2019

I would rate 5 if the course wasn´t so focused on graphic analysis. But, even Like that it´s a very good experience.

por David B

25 de mai de 2017

It was a lot of material in a short time frame, but I feel like I really have a good grasp of creating graphs in R.

por Olav N

22 de jun de 2020

A very well organized course with video lessons that inspire to further exploration of the data analysis topic.

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.