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.
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."
автор: Giovanna A G•
You will learn how to use a very valuable tool in this class; its name is R Markdown. Besides Prof. Peng explains very well the importance of reproducible research. Nice course!
автор: Kim K•
Very helpful and informative information on how to create reproducible research. The project gives you an opportunity to create reproducible research in the format of a report.
автор: Antonio C d S P•
While I'm pretty sure this course is VERY important for researchers, it is not very useful for my area (IT) and I would like to know this before taking the course. Thank you.
автор: Greg A•
This is a necessary evil. You can try to do the other classes in the specialization without it, but learning to use R markdown well is hard with out this or a similar class
автор: Manny R•
Enjoyed learning about rMarkdown, caching, and RPubs. Was also able to spend time plotting and aggregating data in different ways. Didn't enjoy cleaning data too much :)
автор: demehin I•
it shows how to better communicate one analysis and i have learnt a lot from it. the lectures should be updated as some details and figures were irrelevant a this time
автор: Mikhail S•
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.
автор: Jorge E M O•
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.
автор: Jo S•
Covers some important and interesting areas and is generally well taught (although the recording quality on the videos varies). Interesting final project!
автор: Rouholamin R•
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.
автор: Kaplanis A•
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
автор: Luiz C•
Interesting course, but course assginments lack guidance, have too much complexity and require a time spent too long compared to the benefits
автор: Brett A•
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.
автор: Alex F•
Good principles, lectures are improving but still a bit dry and very boring slides. I learned more from my peer reviews than anything else.
автор: BIBHUTI B P•
Good explication of reproducible analysis and representation of didactic approached towards it.
Thank you & keep up the tutoring skills...
автор: Patrick S•
Good course as part of the data science specialization. Much effort needed for assignments in contrast to this relative light topic.
автор: Robert M•
Very good course. Would love to get to see examples of some advanced usage of knitr in developing presentations and complex reports.
автор: Naeem B•
At first this course seems boring but have realized importance after seeing bio statistic prescription drug video of week 4.
This course provides me with some new ideas about reproducible research and allows me to learn how to wrie .Rmd files.
автор: Tim S•
This was another very useful course in the series, with (peer reviewed) assignments taking on a very significant role.
автор: Minki J•
peer assignment is tough, hard and great to learn.
but the course is very general, not that related to the assignment
автор: Igor T•
Good course. Especially enjoyed final course project. It's really challenging and looks like a real‑life task.
автор: Mehrdad P•
Course nicely highlighted the importance of reproducible research and the use of markdown and knitr packages.
автор: Sawyer W•
Good course. Nice overview of concepts of reproduciblity and tools for doing so (sweave, knitr, RPubs)
автор: Jason C•
Very good, but maybe not at solid as those before it. Some reproducibility concepts felt a bit vague.