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 Gregorio A A P•
26 de ago. de 2017
Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.
por César A C•
5 de jun. de 2017
I really needed this course to fully understand how to work with R from the raw data to publication. Nice ¡¡
por Jared P•
10 de abr. de 2016
Loved it. The concepts around reproducible research are important. Should be mandatory teaching in school.
por Suryadipta D•
12 de abr. de 2018
well organized and easy-to-understand subject material, shapes up really well towards the specialization.
por Marco C•
25 de feb. de 2018
Very useful course to build a scientific way of thinking, and publishing my work has been very engaging.
por santiago R•
29 de nov. de 2017
Very nice course. R Markdown make everything looks better and understandable for a reproducible research.
por Yasel G S•
4 de ago. de 2016
This course was very important for my work. I learned so much and I want to say thanks to the professors.
por Shreyas G M•
1 de may. de 2016
Excellently designed course! I loved how the course content and assignments were designed and delivered.
por Hsin C C•
6 de oct. de 2021
Good practice from previous sessions to summarize GGplots accordingly and share same practices as well.
16 de abr. de 2018
the best course I have ever come across which gives us an idea about knitter and markdown packages in r
por Mauricio V•
12 de dic. de 2016
excellent course, specially all the topics related to markdown, rpubs. A must for each data scientist.
por Timothy M S J•
29 de nov. de 2016
Great class. It helps frame all that you will do as a Data Scientist. Building blocks. Peng nails it.
por Edwin L A•
13 de ago. de 2017
Excelente, sigo en el proceso muy animado y trabajando duro, ha sido una experiencia muy importante.
por Hampton, B G•
1 de ago. de 2021
I enjoyed this course as it had practical applications to my work as well as my personal interests.
por Jacques d P•
11 de abr. de 2018
How to implement reproducible research is an essential skill for all data scientists. Good course.
por Mihai C•
8 de mar. de 2016
Very pragmatic course, tremendously useful not just for research but also for commercial projects.
por Mathew K•
13 de ene. de 2020
A pretty good coverage on the need for reproducibility and the best practices to make it happen.
por Christoph G•
9 de jul. de 2016
This was really valuable in terms of how to document correctly and produce reproducable reports.
por Bruno R S•
21 de ene. de 2019
A great introduction to basics of scientific method concerning statistics and result reporting.
por Hongzhi Z•
1 de nov. de 2017
Every week contain assignment about making big projects with less video to watch. That's great。
por Md. I H•
4 de jul. de 2017
This course provides insights about how to reproduce the research findings in efficient manner.
por Naren R B•
8 de abr. de 2019
Would definitey recommend this, it covers an important aspect of research for Data Scientists.
por Carlos A C Z•
21 de ago. de 2017
Excellent course. High recommended for people how need make research than must be reproducible
por Yanal K•
28 de may. de 2016
Wonderful course on research principles and the creation of reproducible R reports with knitr.
por Julian M D C•
17 de jul. de 2020
Very helpful course and very important subject. Perhaps the best course in the specialization