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Opiniones y comentarios de aprendices correspondientes a Investigación reproducible por parte de Universidad Johns Hopkins

4.6
estrellas
4,104 calificaciones
597 reseña

Acerca del Curso

Este curso se centra en los conceptos y las herramientas que permiten realizar análisis de datos modernos de forma reproducible. La investigación reproducible se basa en la idea de que los análisis de datos y, en general, las afirmaciones científicas, se publican con sus datos y el código del software para que otros puedan verificar los hallazgos y basarse en ellos. La necesidad de reproducibilidad aumenta drásticamente a medida que los análisis de datos se vuelven más complejos, con conjuntos de datos más grandes y cálculos más sofisticados. La reproducibilidad permite que las personas se centren en el contenido real de un análisis de datos, en lugar de en los detalles superficiales que aparecen en un resumen escrito. Además, la reproducibilidad hace que un análisis sea más útil para otros, ya que los datos y el código que en realidad permitieron llevar a cabo el análisis están disponibles. Este curso se centrará en las herramientas de análisis estadístico alfabetizadas que permiten publicar los análisis de datos en un único documento que permite a otros ejecutar fácilmente el mismo análisis para obtener los mismos resultados....

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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526 - 550 de 579 revisiones para Investigación reproducible

por Rose G

31 de mar. de 2020

Good introduction to Rpubs, and important remainder of the importance of reproducible research for scientists, but it may be a bit too much to focus an entire course only on that.

por Michał M

28 de ene. de 2016

Some of the videos has low quality, which make them harder to understand for non native speakers. In my opinion there is also too less tips for second assessment.

por Oña G L E

23 de ago. de 2018

The videos doesn't listen well, and some activities are not interesting, you could teach swave and some of latex instead of repeat some parts of other courses.

por BAUYRJAN J

1 de sep. de 2017

This course has contents that are repeated multiple times throughout the course. I think entire course could have been covered in a week or at most two weeks.

por Joseph C

8 de feb. de 2016

The first week assignment should really be the second week assignment since all the lessons about knitr would have made the assignment much easier.

por Andreas S J

4 de oct. de 2017

Important and interesting stuff - but lots of it is repeated too much, which make it seem like 4 weeks is too much for the material.

por Fabiano S

7 de mar. de 2016

It's, for sure, a necessary content but don't feel like something that deserves to be on this specialization. Content is good.

por James O

31 de oct. de 2016

Interesting material, but wasn't necessarily of the same depth of knowledge like previous courses in the series

por Fabiola J C

9 de ene. de 2021

I experience that the course does not cover all the necessary tools to tackle the final assignment with ease.

por Diego T B

17 de nov. de 2017

This topic is very interesting. But I think that was very large and without as practical things in videos.

por Robert K

12 de jun. de 2017

This information is useful, but it felt like this could have been condensed in to a couple of weeks.

por Raushon K

17 de feb. de 2016

Week1 can be explained better. First assignment i was clueleass on Kintr and how to generate report.

por Nathan M

11 de jun. de 2016

Why is this its own class? Seems like it could have been covered in a week somewhere else.

por Jingqin L

28 de abr. de 2021

Cover some essential issue in reproducible research but don't touch much on some details.

por Rohit S A

20 de oct. de 2016

Not a well structured course. Also, not very motivating to go through this one.

por Fernando M

4 de sep. de 2017

Don´t like this topics but I understand that they are necessary. Course is ok

por Corbin C

23 de abr. de 2018

Good material, but some of it is out of date (like deprecated functions).

por Shuwen Y

9 de jul. de 2016

content is not enough for one class. should be only one to two videos.

por Martin G

3 de ago. de 2019

Interesting content. However, it can get somewhat repetitive.

por Raul M

16 de ene. de 2019

Many times the course goes over the same topic over and over.

por Manuel E

29 de abr. de 2019

Good - Makes you assimilate the concept and work on it

por Francesca A

23 de oct. de 2016

That's the best course of the entire specialisation.

por Steph L

26 de ene. de 2021

The guidelines for project 2 need to be improved.

por Marcela Q

26 de nov. de 2019

A little repetitive and basic but useful!!!!

por Lakshay S

13 de jul. de 2019

Pathetic It was . Not at all Interesting !!