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Opiniones y comentarios de aprendices correspondientes a Reproducible Research por parte de Universidad Johns Hopkins

4.6
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3,951 calificaciones
564 reseña

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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....

Principales reseñas

AA
12 de feb. de 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 de ago. de 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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201 - 225 de 547 revisiones para Reproducible Research

por Lei S

27 de dic. de 2017

Only thing: maybe some lectures should be updated.

por phani v k

7 de ene. de 2017

This is a very good course for a begineer like me.

por Laro N P

2 de may. de 2018

Good course. Every new course is a new challenge.

por Shivanand R K

21 de jun. de 2016

Great and Excellent thoughts and course material.

por Mickey K

18 de ago. de 2020

Great course. very important for any researcher.

por Nguyen T T

8 de may. de 2017

The course very good for beginner data scientist

por ILLYA B

12 de oct. de 2020

The best course of John Hopkins Specialization!

por Akram N

2 de may. de 2019

Very fruitful. I enjoyed this lesson very much.

por Jamie M

26 de oct. de 2018

Good course. Does exactly what it says it does.

por Utku K

14 de nov. de 2016

Good lesson, about an interesting topic for me.

por Predrag M

13 de mar. de 2016

One of the best courses in this specialization.

por Bipin K

10 de feb. de 2016

great one to know how about researches are done

por Leonardo R d L P

29 de jul. de 2020

Excelent, very straight foward and informative

por Lingareddygari U R

30 de jun. de 2020

A must course for any data science enthusiast.

por Martin D

28 de oct. de 2018

Great course, great lecture and great content.

por Solomonov A

19 de ene. de 2017

Great course. Make you think like a scientist.

por Hemanth P M

16 de may. de 2016

good course. I will recommend it for everyone.

por Anil G

14 de may. de 2018

One of the best learning contents, great cour

por Harsha v s p B

10 de oct. de 2020

Amazing course so far in the specialization.

por Javier E S

20 de may. de 2018

Excellent course. A lot of issues to learn .

por ooi s m

10 de jun. de 2017

detailed explanation with practical hands-on

por Blaž Z

27 de ago. de 2019

Very nice project at the end of the course!

por Changkeun K

1 de ago. de 2017

very useful and challenge but so memorable.

por Vitalii S

27 de jun. de 2017

I enjoyed this one so much! Give me more...

por Connor B

19 de ago. de 2019

Course Project 2 was fun and learned a lot