Skip to main content

Callysto and Computational Thinking


About This Course

Are you an educator who wants to introduce computational thinking into your classrooms but are unsure where to begin? Jupyter Notebook technology allows you to seamlessly bring together descriptive text, multimedia, open data and live Python programming code to create interactive educational resources across all subject areas that feature computational thinking.

This course developed by the people behind the Callysto program ( starts with an introduction to the fundamentals of computational thinking and shows you how you can bring it into your classrooms using Jupyter Notebook technology and learning resources developed by Callysto. This course will teach you how to run live Python programming code in a non-intimidating manner designed for non-coders, and will build your confidence in interacting with this pervasive technology. This course also provides you with the tools to become your own creator to introduce computational thinking in your own classrooms across all subject areas.

No previous programming knowledge needed. Please join us as you start your computational thinking journey.


This is an introductory course recommended for Grade 5-12 educators with no prerequisites except a curiosity to learn.

Course Team

Michael Lamoureux

Michael Lamoureux is a Professor of Mathematics at the University of Calgary who serves as the Innovation Coordinator of PIMS. Lamoureux has previously served as Chair of the Department of Mathematics and Statistics at the University of Calgary. Lamoureux has an active research program at the interface of harmonic analysis, wave propagation, and numerical methods with applications to problems in geoscience. Courses in complex variables and industrial mathematics leveraging Jupyter have been developed and delivered by Lamoureux. Lamoureux is also the lead author of an e-book on Jupyter and the platform’s usage in teaching and research.

Byron Chu

Byron graduated from the University of Calgary with a PhD in Biochemistry. His studies focused on intrinsic properties of proteins, and today he applies the same scientific principles to data and network-enabled projects. As a burgeoning data scientist, Byron is interested in the intersection of data analysis and storytelling, and how numbers can inform on every level of society: from networks and the environment, to the health issues we may potentially face.

Frequently Asked Questions

What web browser should I use?

The Open edX and Jupyter platforms work best with current versions of Chrome, Firefox, and Edge.

  1. Course Number

  2. Classes Start

  3. Classes End

  4. Estimated Effort

    3 hours per week (9 hours total)