Jupyter notebook for teaching physics

Mike Croucher

EPSRC Research Software Engineering Fellow

How did I get here?

April 2015: Jim Weston

May: iPEG

May->September: Managed Desktop Hell

October: Jupyter for Bioinformatics teaching (Marta Milo)

Online demo:

https://cloud.sagemath.com/#projects/3999d983-e8aa-463c-869a-60500d95d82c/files/KronigPenney.html

Jupyter: What is it?

• Open
• Text, maths, results and code combined
• Interactive research papers
• Interactive lecture notes
• Conversion to .pdf, .html, etc is trivial
• Pervasive computation

Jupyter: In use at Sheffield

• PHY235 Introduction to Python Programming
• PHY241 Introduction to observational astronomy
• PHY340/350 Professional Skills in Physics and Astronomy
• COM4509/COM6509 Machine Learning and Adaptive Intelligence
• COM2004/COM3004 Data Driven Computing
• BMS353 Bioinformatics for Biomedical Science

Some benefits of Jupyter notebook

• Frictionless code execution
• Free
• Works on Raspberry Pi to supercomputers.
• All Operating systems.
• Students can work anywhere, on any device, locally or in cloud

Managed desktop hell

The solution

SageMathCloud Demo

https://cloud.sagemath.com/projects

SageMathCloud benefits

• Jupyter with R, Python, Julia and Sage
• Linux terminal access
• Easy course administration
• Students only need a browser
• Open Source
• Superb support
• Automatic back-ups
• Inexpensive

SageMathCloud usage

The Future?

• Fully interactive, computable lecture notes for the entire syllabus
• e.g. Fourier series

Next steps

• SageMathCloud seminar for lecturers
• Jupyter on Iceberg (Sheffield HPC)