Learner Reviews & Feedback for Reproducible Research by Johns Hopkins University
About the Course
Top reviews
AA
Feb 12, 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
Aug 19, 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."
376 - 400 of 582 Reviews for Reproducible Research
By 刘博
•Mar 2, 2017
good work
By Carlos R
•Dec 26, 2016
Excelente
By saroj r
•May 14, 2016
i like it
By 杜冈桃
•Oct 7, 2017
Perfect
By Sanjay B
•Oct 27, 2020
Great.
By Medha B
•Oct 18, 2020
Great.
By Adán H
•Nov 6, 2017
thanks
By Zhao M
•Nov 1, 2016
good.
By manoj k
•Aug 31, 2016
Great
By Chandan K S
•Nov 13, 2020
nice
By �SADHARAN G
•Jul 17, 2020
good
By Rizwan M
•Sep 5, 2019
good
By SriHari a
•Apr 21, 2019
Good
By Amit K R
•Nov 27, 2017
Good
By Jay B
•Aug 24, 2017
Good
By Yi-Yang L
•Apr 10, 2017
Good
By Oleksandr F
•Nov 24, 2016
Nice
By 朱荣荣
•Mar 11, 2016
good
By Meidani P
•Dec 3, 2021
-
By Suriya
•Feb 24, 2018
O
By Marat G
•Mar 22, 2017
)
By Jeffrey P
•Mar 15, 2016
By far the most time consuming, yet rewarding course in the data science specialization thus far. Literate Programing in general and R Markdown in particular are simple enough as concepts, but do take some time to grow accustomed to. However, I found the course to be a compelling argument for reproducibility that has application beyond just Data Science proper.
Although the technology is completely different, the concepts behind reproducibility really resonated with me and the work I do managing a division in Application Development. I'm constantly having to balance seemingly limitless demands, limited resources, and the difficulty of retaining staff in highly-competitive industry. Reproducibility becomes not just the basis for cross-training, product stabilization, and growth, but is a necessary ingredient of a team's survival.
This course not only cemented my own thoughts on the topic, but gave me some new ideas and tools for process improvement on the job.
By Nicolas L
•Apr 15, 2020
El proyecto final del curso tiene poco que ver con lo enseñado a lo largo de éste, era muy necesario haber tomado los cursos anteriores (en especial R programming y Exploración de Datos). Además, el proyecto debería estar mejor planificado, se buscaba que la mayor parte del tiempo estuviera en limpiar la data? O un objetivo más fuerte era el uso de gráficos más elaborados u otro al interior de RMarkdown? O un análisis un poco más elaborado que sólo sumar?
By Siying R
•Oct 21, 2018
This course teaches how to present a R code analysis that others can run the code to reproduce the same result. The length of the lecture is minimum and the project helps me to make the reproducible analysis on my own. One thing I would like to see improvement is that the instructor's speech. I hope that he can speak more smoothly without stopping to repeat words. It was quite a struggle to listen to his talking. Thank you.
By Travis M
•Apr 2, 2016
The first assignment should occur during the second week instead of the first given how the material is presented. The second and final project is very time consuming. Ideally this course should run for 6 weeks instead of 4 because of this. The second project is challenging and it definitely drives home the point about reproducible result given the state of the raw data.
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