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Learner Reviews & Feedback for Reproducible Research by Johns Hopkins University

4,160 ratings

About the Course

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results....

Top reviews


Feb 12, 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 19, 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."

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426 - 450 of 586 Reviews for Reproducible Research

By Jorge E M O

Jul 21, 2016

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

Jan 27, 2016

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

May 12, 2019

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

Dec 26, 2016

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

Sep 17, 2017

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

Apr 24, 2016

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

Jan 17, 2018

Good principles, lectures are improving but still a bit dry and very boring slides. I learned more from my peer reviews than anything else.


May 30, 2017

Good explication of reproducible analysis and representation of didactic approached towards it.

Thank you & keep up the tutoring skills...

By Patrick S

Feb 9, 2017

Good course as part of the data science specialization. Much effort needed for assignments in contrast to this relative light topic.

By Robert M

Dec 12, 2016

Very good course. Would love to get to see examples of some advanced usage of knitr in developing presentations and complex reports.

By Chris R

Jan 4, 2022

Great course. Some of the materials are now a bit dated, but I really appreciated the content and the projects to skill-build.

By Naeem B

Jun 22, 2018

At first this course seems boring but have realized importance after seeing bio statistic prescription drug video of week 4.


Dec 19, 2018

This course provides me with some new ideas about reproducible research and allows me to learn how to wrie .Rmd files.

By Deleted A

May 30, 2016

This was another very useful course in the series, with (peer reviewed) assignments taking on a very significant role.

By Minki J

Jan 1, 2018

peer assignment is tough, hard and great to learn.

but the course is very general, not that related to the assignment

By Igor T

Feb 26, 2017

Good course. Especially enjoyed final course project. It's really challenging and looks like a real‑life task.

By Mehrdad P

Sep 26, 2019

Course nicely highlighted the importance of reproducible research and the use of markdown and knitr packages.

By Sawyer W

Aug 1, 2017

Good course. Nice overview of concepts of reproduciblity and tools for doing so (sweave, knitr, RPubs)

By Jason C

May 6, 2016

Very good, but maybe not at solid as those before it. Some reproducibility concepts felt a bit vague.

By Nicolás H

Sep 13, 2020

Necesario para conocer, emplear buenas prácticas y darle validez científica a los trabajos realizados

By Asif K

Sep 17, 2018

Very good content and pace. Got good hands on experience, right content and structure of assignments

By Brian F

Jul 8, 2017

Although there is not a lot to this course I like that it covers an area that is often neglected.

By Jeremy J

Sep 11, 2016

Some of the material seems pretty rote but it did introduce some new software and capabilities.

By Luiz E B J

Oct 21, 2019

This is a good course tht open our minds and eyes to the relevance of Reproducible Research.

By Joseph F

Jan 13, 2021

Now I appreciate what is the importance of a reproducible research! Awesome course overall!