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."
por Gabriel O M•
very nice, I learned new stuff that I didn't know. Very easy to follow and to understand as well. The exercises and projects are really good to practice previous knowledge acquired. Also I'm pretty sure that this course will help me out in my tasks at my current work.
por Camilla H•
The course finally got me to use markdown files which I had dabbled with before. It was nice to cement some knowledge. What I didn't appreciate was the largely redundant video lectures. Some were what seemed to be the same lecture given a year or two apart.
por Kyle H•
A few of the lectures were a bit repetitive if you are taking the full data science specialization. Overall there are some valuable skills and thought patterns that will prove useful if interested in reproducibility and clarity of analysis.
por Mengyin B•
It is about how to make your work available for others and yourself in the future. It is quite refreshing because I have never heard about anything in this course from anywhere else. It is useful for me and hope it will be useful to you.
por 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.
por 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?
por 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).
por 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.
por 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!
por 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.
por 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.
por 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
por 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 :)
por 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
por 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.
por 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.
por Jo S•
Covers some important and interesting areas and is generally well taught (although the recording quality on the videos varies). Interesting final project!
por 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.
por 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
por Luiz C•
Interesting course, but course assginments lack guidance, have too much complexity and require a time spent too long compared to the benefits
por 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.
por 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.
por BIBHUTI B P•
Good explication of reproducible analysis and representation of didactic approached towards it.
Thank you & keep up the tutoring skills...
por Patrick S•
Good course as part of the data science specialization. Much effort needed for assignments in contrast to this relative light topic.
por Robert M•
Very good course. Would love to get to see examples of some advanced usage of knitr in developing presentations and complex reports.