Labs
Hands-on lab notebooks that run in the class JupyterHub on the GPU box. Click Launch to open a lab. It pulls the latest version into your account and opens the notebook. The first time, sign in with your class account. Each lab’s details page has its description and a direct launch button.
Get comfortable driving the machine from the command line before you build on it. A hands-on tour of the most useful Linux commands for finding your way around, working with files, searching text, and checking on the system.
Every lab after this one runs Python inside a Jupyter notebook, so spend an hour getting fluent first. Practice running cells, tracking what the notebook remembers, and reading and editing small pieces of Python before the real builds begin.
Design a repeatable experiment and turn it into clean, reproducible data. Simulate realistic edge measurements like latency, power, and temperature, decide how many runs an experiment needs, record the results in a tidy format, and pin the whole thing with a virtual environment so anyone can reproduce it.
Turn experiment data into figures you could put in a paper. Pick the right chart for each claim, apply one consistent house style, keep colors readable for colorblind and grayscale readers, and export clean vector files ready for a report or LaTeX.
Build and run your first containers, then wire a few together into a small edge system. This is the sandbox every later lab builds on, so you leave comfortable starting, inspecting, and tearing containers down.