Feb 13, 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.
Aug 20, 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."
автор: Daniel C J•
Nov 14, 2016
Great course. A must for every analyst for its simple tips on reproducibility, which can go a very very long way at work or school
автор: Omar N•
Nov 08, 2018
Really good module/course, gives you a glimpse into real world implementation of data science and the challenges involved with it.
автор: ONG P S•
Jan 19, 2020
Very practical and knowledge learned can be applied into my works as auditors. This can benefit any fields involving using data.
автор: Donald J•
Jan 22, 2018
These are important skills for a data scientist and I'm glad there is a full 4-week course dedicated to reproducible research.
автор: Richmond S•
Sep 29, 2016
I struggled in getting the final project right but it helped me understand the course better. Thumbs up reproducible research
автор: PRAKASH K•
Jul 13, 2020
I strongly recommend this course ,it focuses on reproducible research which is equally an important aspect of data analysis.
автор: Glenn W•
Mar 04, 2019
Favorite course so far. Really enjoyed working on the projects. They were very helpful in helping to reinforce the material.
автор: Amanyiraho R•
Jan 13, 2020
Very interesting and tackles a very important issue that Data scientists always miss-out, reproducibility of your project
автор: Azat G•
Jan 24, 2019
Amazing course, it introduced the concepts of reproducibility which is used to provide scientific fairness, transparency.
автор: Anusha V•
Jan 03, 2019
Excellent Course - particular useful for anyone doing research and performing any kind of analysis on the observed data.
автор: Adrielle S•
Apr 03, 2016
Muito completo. Inglês claro. Muitos exemplos. Chega a ser repetitivo em algumas aulas mas, antes sobrar do que faltar!
автор: Krishna B•
May 30, 2017
towards the end of week 1 lectures we can see all the parts of this specialization coming together in a very nice way!
автор: Prem S•
Aug 02, 2017
Nice course,especially it gives you a general idea and foundation on r markdown files if you already know R studio.
автор: Federico A V R•
Jul 27, 2017
This topic is relevant to the field, yet few institutions offer courses on it. Great knowledge, highly recommended.
автор: Lee Y L R•
Feb 02, 2018
Clear sharing of the importance of having proper documentation of data analysis process to enable reproducibility.
автор: Ann B•
Mar 14, 2017
I think this topic is sometimes overlooked, but very necessary. This course did a good job of covering the topic.
автор: Emily S•
May 18, 2016
I think this is an essential course that more people should take. Reproducibility is a huge issue in many fields.
автор: Courtney R•
Oct 07, 2019
I really appreciated the topics covered in this course. Is a wonderful follow-up to the Exploratory Data course.
Aug 12, 2019
course material and projects help a lot in learning and tips on how to better document research and projects
автор: Gregorio A A P•
Aug 26, 2017
Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.
автор: César A C•
Jun 05, 2017
I really needed this course to fully understand how to work with R from the raw data to publication. Nice ¡¡
автор: Jared P•
Apr 10, 2016
Loved it. The concepts around reproducible research are important. Should be mandatory teaching in school.
автор: Suryadipta D•
Apr 12, 2018
well organized and easy-to-understand subject material, shapes up really well towards the specialization.
автор: Marco C•
Feb 25, 2018
Very useful course to build a scientific way of thinking, and publishing my work has been very engaging.
автор: santiago R•
Nov 29, 2017
Very nice course. R Markdown make everything looks better and understandable for a reproducible research.