Chevron Left
Back to Reproducible Research

Learner Reviews & Feedback for Reproducible Research by Johns Hopkins University

4.6
stars
4,178 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

AP

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.

RR

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."

Filter by:

201 - 225 of 589 Reviews for Reproducible Research

By Dorian P

•

May 8, 2017

Very nice course, learn a lot with it. Thank you very much.

By Bhavneet S

•

Jun 29, 2023

It's a great introductory course to Reproducible research.

By carl w

•

Jul 9, 2018

Knitr was a nice tool to learn. I can see it being useful.

By V P

•

Jul 3, 2018

most nicely designed course in the specialization loved it

By Andrew

•

Apr 7, 2019

One of my favorite courses in the specialization so far.

By Andreas K

•

Dec 12, 2016

best course so far in the data scienist course package!

By James W

•

Oct 31, 2016

This course helped me very much with my current career.

By Md G M

•

Jul 30, 2018

Course contents are very good and easy to understands.

By Massimo M

•

Feb 15, 2018

Very nice course, easy to follow and very well taught.

By Giovanni M C V

•

Feb 16, 2016

Excellent course with great didactic. Congratulations!

By Chanpreet k

•

Dec 30, 2018

Good course content. All things explained quite well.

By Dewald O

•

Oct 31, 2018

Such a great course! The instructors are really good.

By César A

•

Jun 16, 2020

Very nice program and a lot of practical exercices

By Mohammad A

•

Jul 20, 2018

Great course , very informative and well organized

By Lei S

•

Dec 27, 2017

Only thing: maybe some lectures should be updated.

By phani v

•

Jan 7, 2017

This is a very good course for a begineer like me.

By Laro N

•

May 2, 2018

Good course. Every new course is a new challenge.

By Shivanand R K

•

Jun 21, 2016

Great and Excellent thoughts and course material.

By מיקי כ

•

Aug 18, 2020

Great course. very important for any researcher.

By Trung N T

•

May 8, 2017

The course very good for beginner data scientist

By Damian S

•

Nov 16, 2021

Interesting course with well prepared exercises

By Deleted A

•

Oct 12, 2020

The best course of John Hopkins Specialization!

By Akram N

•

May 2, 2019

Very fruitful. I enjoyed this lesson very much.

By Jamie M

•

Oct 26, 2018

Good course. Does exactly what it says it does.

By Utku K

•

Nov 14, 2016

Good lesson, about an interesting topic for me.