AP
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."
By Mikhail S
•Feb 6, 2016
First week has an assignment that requires knowledge from the second week. It would be better for the course if both assignments has two weeks for accomplishment.
By Jorge E M O
•Jul 21, 2016
The course already needs and actualization, plus they must fix the order of the first assignment. Besides that, this is a really useful and fulfilling course.
By Jo S
•Jan 27, 2016
Covers some important and interesting areas and is generally well taught (although the recording quality on the videos varies). Interesting final project!
By Rouholamin R
•May 12, 2019
lectures are a little bit theoretical and at some point maybe boring but projects will give you a real experience with data and research reproducibility.
By Kaplanis A
•Dec 26, 2016
All in all a great course with very valuable information to make a data scientist better at his job. However it could have been covered in 2 weeks time
By Luiz C
•Sep 17, 2017
Interesting course, but course assginments lack guidance, have too much complexity and require a time spent too long compared to the benefits
By Brett A
•Apr 24, 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.
By Alex F
•Jan 17, 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.
By BIBHUTI B P
•May 30, 2017
Good explication of reproducible analysis and representation of didactic approached towards it.
Thank you & keep up the tutoring skills...
By Patrick S
•Feb 9, 2017
Good course as part of the data science specialization. Much effort needed for assignments in contrast to this relative light topic.
By Robert M
•Dec 12, 2016
Very good course. Would love to get to see examples of some advanced usage of knitr in developing presentations and complex reports.
By Chris R
•Jan 4, 2022
Great course. Some of the materials are now a bit dated, but I really appreciated the content and the projects to skill-build.
By Naeem B
•Jun 22, 2018
At first this course seems boring but have realized importance after seeing bio statistic prescription drug video of week 4.
By LIWANGZHI
•Dec 19, 2018
This course provides me with some new ideas about reproducible research and allows me to learn how to wrie .Rmd files.
By Deleted A
•May 30, 2016
This was another very useful course in the series, with (peer reviewed) assignments taking on a very significant role.
By Minki J
•Jan 1, 2018
peer assignment is tough, hard and great to learn.
but the course is very general, not that related to the assignment
By Igor T
•Feb 26, 2017
Good course. Especially enjoyed final course project. It's really challenging and looks like a real‑life task.
By Mehrdad P
•Sep 26, 2019
Course nicely highlighted the importance of reproducible research and the use of markdown and knitr packages.
By Sawyer W
•Aug 1, 2017
Good course. Nice overview of concepts of reproduciblity and tools for doing so (sweave, knitr, RPubs)
By Jason C
•May 6, 2016
Very good, but maybe not at solid as those before it. Some reproducibility concepts felt a bit vague.
By Nicolás H
•Sep 13, 2020
Necesario para conocer, emplear buenas prácticas y darle validez cientÃfica a los trabajos realizados
By Asif K
•Sep 17, 2018
Very good content and pace. Got good hands on experience, right content and structure of assignments
By Brian F
•Jul 8, 2017
Although there is not a lot to this course I like that it covers an area that is often neglected.
By Jeremy J
•Sep 11, 2016
Some of the material seems pretty rote but it did introduce some new software and capabilities.
By Luiz E B J
•Oct 21, 2019
This is a good course tht open our minds and eyes to the relevance of Reproducible Research.