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

4.6
étoiles
4,113 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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126 - 150 sur 580 Avis pour Recherche reproductible

par Gregorio A A P

26 août 2017

Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.

par César A C

5 juin 2017

I really needed this course to fully understand how to work with R from the raw data to publication. Nice ¡¡

par Jared P

10 avr. 2016

Loved it. The concepts around reproducible research are important. Should be mandatory teaching in school.

par Suryadipta D

12 avr. 2018

well organized and easy-to-understand subject material, shapes up really well towards the specialization.

par Marco C

25 févr. 2018

Very useful course to build a scientific way of thinking, and publishing my work has been very engaging.

par santiago R

29 nov. 2017

Very nice course. R Markdown make everything looks better and understandable for a reproducible research.

par Yasel G S

4 août 2016

This course was very important for my work. I learned so much and I want to say thanks to the professors.

par Shreyas G M

1 mai 2016

Excellently designed course! I loved how the course content and assignments were designed and delivered.

par Hsin C C

6 oct. 2021

Good practice from previous sessions to summarize GGplots accordingly and share same practices as well.

par sneha

16 avr. 2018

the best course I have ever come across which gives us an idea about knitter and markdown packages in r

par Mauricio V

12 déc. 2016

excellent course, specially all the topics related to markdown, rpubs. A must for each data scientist.

par Timothy M S J

29 nov. 2016

Great class. It helps frame all that you will do as a Data Scientist. Building blocks. Peng nails it.

par Edwin L A

13 août 2017

Excelente, sigo en el proceso muy animado y trabajando duro, ha sido una experiencia muy importante.

par Hampton, B G

1 août 2021

I enjoyed this course as it had practical applications to my work as well as my personal interests.

par Jacques d P

11 avr. 2018

How to implement reproducible research is an essential skill for all data scientists. Good course.

par Mihai C

8 mars 2016

Very pragmatic course, tremendously useful not just for research but also for commercial projects.

par Mathew K

13 janv. 2020

A pretty good coverage on the need for reproducibility and the best practices to make it happen.

par Christoph G

9 juil. 2016

This was really valuable in terms of how to document correctly and produce reproducable reports.

par Bruno R S

21 janv. 2019

A great introduction to basics of scientific method concerning statistics and result reporting.

par Hongzhi Z

1 nov. 2017

Every week contain assignment about making big projects with less video to watch. That's great。

par Md. I H

4 juil. 2017

This course provides insights about how to reproduce the research findings in efficient manner.

par Naren R B

8 avr. 2019

Would definitey recommend this, it covers an important aspect of research for Data Scientists.

par Carlos A C Z

21 août 2017

Excellent course. High recommended for people how need make research than must be reproducible

par Yanal K

28 mai 2016

Wonderful course on research principles and the creation of reproducible R reports with knitr.

par Julian M D C

17 juil. 2020

Very helpful course and very important subject. Perhaps the best course in the specialization