This day contains a real Neuromatch Academy tutorial converted from its original Jupyter notebook format into MyST Markdown. It demonstrates what production course content looks like in a course built with the kit.
The tutorial below was originally W2D3_Tutorial1: Linear Dynamical Systems from the NMA Computational Neuroscience course. All elements -- videos, exercises, solutions, interactive widgets, and feedback widgets -- have been preserved and reformatted into MyST syntax.
Tutorial 2 is the same tutorial as a scrollytelling page: a pinned stage of figures, videos and live Python beside text cards that scroll past. Open the two side by side to compare the layouts, and see W1D2 Tutorial 6 for how it is built.
Learning objectives¶
By the end of this tutorial you will be able to:
Simulate the trajectory of a dynamical system using forward Euler integration
Understand the behavior of one-dimensional linear dynamical systems
Understand the dynamics of two-dimensional linear systems using eigenvalues and eigenvectors
Interpret stream plots of two-dimensional systems
Schedule¶
| Tutorial | Topic | Duration |
|---|---|---|
| Tutorial 1 | Linear dynamical systems | 1 hour |
| Tutorial 2 | Linear dynamical systems (scrollytelling version) | 1 hour |