First time? Follow the sheet Getting started, click by click (PDF).
Click Open in Colab on a notebook, then Copy to Drive, and work in your copy.
No Google account? Use JupyterLite (Python runs in your browser; download your work before leaving).
Session 1: the cyclist's twin
0 - First steps in Google ColabColab link soon JupyterLite
1 - Python basics with sport numbersColab link soon JupyterLite
2 - The critical power testColab link soon JupyterLite
3 - A simple digital twin, simulated second by secondColab link soon JupyterLite
4 - Measurements are never perfectColab link soon JupyterLite
5 - Mini-project: coach for a dayColab link soon JupyterLite
Session 2: pacing a 1500 m
6 - Running a 1500 m: simulate the raceColab link soon JupyterLite
7 - Mini-project: the pacing challengeColab link soon JupyterLite
Session 3: learning from data
8 - Learning from examples: random forest and neural networkColab link soon JupyterLite
9 - A physics-informed neural networkColab link soon JupyterLite
10 - Mini-project: physics or data?Colab link soon JupyterLite
Open JupyterLite (all notebooks) Download all notebooks (zip)
Session 2 uses the runner model of Aftalion & Trélat (2021), J Math Biol 83:9. Session 3: random forest, neural network and physics-informed neural network. Everything runs in the browser: nothing to install.