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

4.7
étoiles
5,836 évaluations
845 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

Y
23 sept. 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!

CC
28 juil. 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.

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776 - 800 sur 814 Avis pour Exploration analytique de données

par Dylan P

13 mai 2018

I would have liked an assignment to focus on the clustering methods and I think dimension reduction was reviewed way too quick.

par ozan b

5 févr. 2017

Course is good in general but "HIERACHICAL CLUSTERING" part is hard to understand and is not clear, should be explained more.

par Casey B

12 mai 2016

Good class - links and slides have not been updated recently. Frustrating to finish without the exact linkts to the data.

par Katharine R

3 mai 2016

Good course, but the SWIRL exercises (and a few quiz questions) needed to be updated for the latest version of ggplot2.

par Johnny C

6 mars 2018

In general was good, but there were some lectures and exercises which were disorganized ("plots with colors")

par Erkan E

24 juin 2016

I wish there several comprehensive examples of exploring some real data as guided by the course instructors.

par Mehrdad P

25 août 2019

The course was overall ok, but I wish discussions about k-means, PCA and SVD were divided into two courses.

par Daniel P

8 déc. 2019

I've learned plotting in R. I expect to learn more in four weeks of "Data Science" specialization.

par Stuart A

18 juil. 2020

Course hasn't been updated in a long time, some of the data needed for the projects has migrated.

par Francisco M R O

8 janv. 2019

The third and fourth week were a big leap in knowledge and not really well explained, for me.

par sandeep d

10 mars 2018

Excercises are very good. But I believe lecture could be more interesting and easily taught.

par Guy P

26 mars 2016

It misses an assignment which will allow to practice the clustering skills.

par Alex s

17 janv. 2018

It focus too much on the tools and a little bit on the analysis

par Amit O

30 sept. 2017

faced many technical difficluties in pratcice exerices in swirl

par Eduardo V K

28 juin 2020

There seems to be some outdated info in several tests.

par Rafael A

23 mars 2017

First two weeks are too repetitive with other courses

par Kevin F

15 juil. 2020

pretty brief and basic. no assessment on clustering.

par Erwin V

12 mars 2016

Interesting stuff, but not a lot of detail

par Oscar P G P

17 sept. 2020

It's necessary for more examples!!!!

par Lidiya N

28 avr. 2019

Absolutely No technical help, like insane amounts of homework for each week. People have jobs and businesses to run. Incredibly short duration. Like literally this should have been spread out several more weeks. I would have dropped the class but I can’t. It’s so difficult to get i to the first set of practice assignments and these several sets. Honestly, I am literally getting no help on it and probably won’t pass because I am missing the deadline. I finished 5 coursera courses working on them for 24 none stop. I’ve literally been at this class all day. Besides all the insane amounts of assignments there’s tons of videos to watch and uploads to do. Go buy some books or take another class unless you are unemployed or have nothing better to do.

par Matt C

14 janv. 2021

These courses need to be updated.

At least one of the Swirl packages references a retired command, gather.

The use of Swirl is nice but it can get very tiring when the computer picks up spaces and makes correct small details over and over.

I believe that all of these courses need to share some practice questions before the quizzes. This allows people to discuss the problems they have without feeling like you are cheating when discussing quiz questions.

Six years is a long time to have course material for teaching. I suggest it is getting too OLD.

par Jesús A P G

20 juil. 2020

More than Exploratory data analysis, the course is only focused on how to make graphs in R. That is actually fine, but the name of the course is not suited to the content. In addition, the lectures were too boring. The lack of pedagogy is stunning. The most useful part of the course was the swirl exercises that were the same examples shown in the lectures. That is why it seems that watching video lectures is an incredible waste of time.

par Jamie R

6 juin 2019

Just an extended course on using R. There was little strategies for Exploratory Data Analysis, infact the example jumped from a high level view of the data to then start looking at individual counties. There are multiple tools in the market that will deliver in a better and faster way for exploratory data analysis. This course should be more targeted at developing a skill set that is tool agnostic.

par Joseph M K

31 janv. 2017

Clustering topic is covered superficially, too much time spend on employing ggplot graphs, not very useful since making graphs is straightforward on other software, like excel, once you aggregate datasets correctly. I had not found it very enriching as a course. I would merge this class within R-Programming section and call it Part 2 rather than categorizing into "Exploratory Data Analysis".

par Bartlomiej W

6 févr. 2016

Some parts of material is good quality, but some is bad - also some show bad practices in R. Extensively use swirl as assignments over self work. It is better to go through good tutorial over R base plotting system and ggplot2.