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."
By Yudhanjaya W•
The lessons on Knitr, Markdown and the case studies dissecting research were useful, but I felt far too little time was spent on examples of implementing reproducible research, and too much time spent talking about its benefits.
By John D M•
Good, but the final project involved too much programming and the size of the data file was unmanageable on my three year old laptop. Could the objectives be met with a smaller data file and less programming?
By Yevgen M•
If you are at university (PhD student, academic, researcher, etc.) then you kind of know most of the "theory". However, practising R was a huge plus (personally, I liked the Week 4 task).
By Yatin M•
Learning Knitr was cool. However, many of the slides were not directly relevant to the course. I think, more rigor can be added, or this course can be merged with one of the others.
By 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!
By 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.
By 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.
By 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
By 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 :)
By 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
By 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.
By 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.
By Jo S•
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•
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•
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•
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•
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•
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•
Good explication of reproducible analysis and representation of didactic approached towards it.
Thank you & keep up the tutoring skills...
By Patrick S•
Good course as part of the data science specialization. Much effort needed for assignments in contrast to this relative light topic.
By Robert M•
Very good course. Would love to get to see examples of some advanced usage of knitr in developing presentations and complex reports.
By 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.
By Tim S•
This was another very useful course in the series, with (peer reviewed) assignments taking on a very significant role.
By Minki J•
peer assignment is tough, hard and great to learn.
but the course is very general, not that related to the assignment