Principles, Statistical and Computational Tools for Reproducible Science

Harvard University on edX

Learn skills and tools that support data science and reproducible research, to ensure you can trust your own research results, reproduce them yourself, and communicate them to others.

About this course

Learn skills and tools that support data science and reproducible research, to ensure you can trust your own research results, reproduce them yourself, and communicate them to others. In this free HarvardX data science course, you’ll learn:

  • Understand a series of concepts, thought patterns, analysis paradigms, and computational and statistical tools, that together support data science and reproducible research.
  • Fundamentals of reproducible science using case studies that illustrate various practices
  • Key elements for ensuring data provenance and reproducible experimental design
  • Statistical methods for reproducible data analysis
  • Computational tools for reproducible data analysis and version control (Git/GitHub, Emacs/RStudio/Spyder), reproducible data (Data repositories/Dataverse) and reproducible dynamic report generation (Rmarkdown/R Notebook/Jupyter/Pandoc), and workflows.
  • How to develop new methods and tools for reproducible research and reporting
  • How to write your own reproducible paper.

 

Type
Short Course
Experience Level
Beginner
Duration
8 weeks
Cost
Free
Topic(s)

Frequently Asked Questions

What is a short course?

With a short course, you’ll typically deep-dive into a specific area of interest within a broader topic.

Short courses are typically between 1 and 12 hours in duration, and in the case of guided courses (i.e. with live instructors), are sometimes spread over a number of days or weeks. Most short courses are self-paced, which means you progress through a series of videos and projects at your own pace.

Depending on the institution and the platform, you may also get a certificate of completion that you can add to your LinkedIn profile.

Is this really 100% online?

This course is completely online, so you can study from anywhere! All you’ll need is a device with an internet connection, such as a computer or a smartphone. If the course has any live, instructor-led sessions, you may need a microphone and possibly a webcam to fully participate. The instructor will make you aware of this beforehand.