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.
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."
por Brett A•
24 de abr. de 2016
Overall I found this course useful. My only complaint is that the material needed to complete the first assignment in week 1 came in week 2.
por Alex F•
17 de ene. de 2018
Good principles, lectures are improving but still a bit dry and very boring slides. I learned more from my peer reviews than anything else.
por BIBHUTI B P•
30 de may. de 2017
Good explication of reproducible analysis and representation of didactic approached towards it.
Thank you & keep up the tutoring skills...
por Patrick S•
9 de feb. de 2017
Good course as part of the data science specialization. Much effort needed for assignments in contrast to this relative light topic.
por Robert M•
12 de dic. de 2016
Very good course. Would love to get to see examples of some advanced usage of knitr in developing presentations and complex reports.
por Chris R•
4 de ene. de 2022
Great course. Some of the materials are now a bit dated, but I really appreciated the content and the projects to skill-build.
por Naeem B•
22 de jun. de 2018
At first this course seems boring but have realized importance after seeing bio statistic prescription drug video of week 4.
19 de dic. de 2018
This course provides me with some new ideas about reproducible research and allows me to learn how to wrie .Rmd files.
por Tim S•
30 de may. de 2016
This was another very useful course in the series, with (peer reviewed) assignments taking on a very significant role.
por Minki J•
1 de ene. de 2018
peer assignment is tough, hard and great to learn.
but the course is very general, not that related to the assignment
por Igor T•
26 de feb. de 2017
Good course. Especially enjoyed final course project. It's really challenging and looks like a real‑life task.
por Mehrdad P•
26 de sep. de 2019
Course nicely highlighted the importance of reproducible research and the use of markdown and knitr packages.
por Sawyer W•
1 de ago. de 2017
Good course. Nice overview of concepts of reproduciblity and tools for doing so (sweave, knitr, RPubs)
por Jason C•
6 de may. de 2016
Very good, but maybe not at solid as those before it. Some reproducibility concepts felt a bit vague.
por Nicolás H•
13 de sep. de 2020
Necesario para conocer, emplear buenas prácticas y darle validez científica a los trabajos realizados
por Asif K•
17 de sep. de 2018
Very good content and pace. Got good hands on experience, right content and structure of assignments
por Brian F•
8 de jul. de 2017
Although there is not a lot to this course I like that it covers an area that is often neglected.
por Jeremy J•
11 de sep. de 2016
Some of the material seems pretty rote but it did introduce some new software and capabilities.
por Luiz E B J•
21 de oct. de 2019
This is a good course tht open our minds and eyes to the relevance of Reproducible Research.
por Joseph F•
13 de ene. de 2021
Now I appreciate what is the importance of a reproducible research! Awesome course overall!
por Shivangi P•
3 de ago. de 2020
It is a nicely structured course with introduction to R and gives a brief of data science.
por Francisco M R O•
9 de mar. de 2019
It was very useful for me, now I know the importance of making data analysis reproducible.
por Korwin A•
6 de feb. de 2016
Great class with excellent supporting material. A little chaotic, but very good overall.
por Amol M•
18 de may. de 2020
This course provides an easy way out to create reports which can be shared with others.
por Thej K•
12 de mar. de 2019
Nothing serious in this course! Rmd is a good tool to work with! and get familiar with!