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Avis et commentaires pour d'étudiants pour Recherche reproductible par Université Johns-Hopkins

4.6
étoiles
4,115 évaluations

À propos du cours

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results....

Meilleurs avis

AA

12 févr. 2016

My favorite course, at least it gives me an argument why scripted statistics is awesome and can be applied to a number of data related activities. Recycling chunks of code has proven useful to me.

RR

19 août 2020

A very important course that greatly improved my ability to communicate the findings of any sort of data analysis that I perform. This is a critical skill to acquire to "deliver the means."

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151 - 175 sur 580 Avis pour Recherche reproductible

par Harsh G

16 mai 2020

Great course, informative videos, challenging Projects and and excellent learning experience.

par Premkumar S

11 nov. 2018

Excellent course! Very good course materials and well thought out quizzes! Highly recommend!!

par Brandon C

17 févr. 2016

One of the most useful classes so far!

Provides great foundation for creating quality reports!

par Trevor G

27 nov. 2019

I thought this was a very helpful class. Brought together the first 4 classes really nicely.

par Luong M Q

27 juil. 2017

It is easy to understand and eventually I could create my own research in a reproducible way

par Sanat N D

8 avr. 2017

I found this course very informative and helpful. The course content is very well organized.

par Manuel M M

21 nov. 2019

Nice course. you learn quite a lot of things although it could be a little bit more complex

par 李俊宏

11 mars 2018

I think this one is very important because scientific research always need to be repeated!

par Talant R

24 oct. 2016

Great course to learn "knitr" and how to code in reproducible manner!

Totally recommend it!

par Eric K

21 juin 2020

Excellent course. Roger Peng is a fantastic instructor and knows R and data science well.

par Giovanni V

10 avr. 2016

This course helped me to apply skills learned in the other courses of the specialization.

par Georgios P

31 oct. 2018

I learned how to write and publish reproducible articles in a very short period of time!

par Juliana C

25 sept. 2017

Great great course to learn basics on reproducibility, and nice R tools like R Markdown

par Wassim K

26 mai 2017

I enjoyed it a lot. the learned material is applicable to any scientific work to be done

par Atair A C j

6 oct. 2017

I was able to learn very good base to assure my work can be reproduced within my peers.

par 陈颐欢

10 juin 2018

The concept introduced here is very essential and basic for high quality data analysis

par Rob S

6 févr. 2020

very interesting, but a pity about the errors that occur due to incompatible software

par Shubham S

24 nov. 2019

Thank you instructors, for making me realize the importance of reproducible research.

par Rodney J

6 juil. 2017

This is a great course on a very important topic that every researcher should master.

par Lindy W

18 déc. 2016

Learnt some really neat new tools. Favourite course from this specialisation so far.

par SUBHOBRATA G

18 sept. 2021

i have copmplete 5 courses but not get specialization certificate from data science

par Stephan H

9 oct. 2017

Nice course. But I'm always worried about the estimated lengths of the assignments.

par Brendan M

28 févr. 2017

This was possibly the most important class I took, which was completely unexpected.

par Sai S

27 juin 2017

Think an assignment after week-3 even if its a fishing expedition would add value.

par Raunak S

11 oct. 2018

great course for those wanting to learn basic concepts of Reproducible Research.