Technical Requirements and Setup

Technical Requirements and Setup#

The Short Version#

The lowest-friction path is a current web browser plus free Google Colab. You do not need to buy software, own a GPU, or install Python to complete the supplied labs. The supplied labs are CPU-compatible; no dedicated GPU is required.

Student Hardware#

Path

Minimum

Recommended

Cost

Colab

Current Chrome, Edge, Firefox, or Safari; stable broadband

8 GB system memory and a keyboard suitable for coding

Free tier is sufficient

GitHub Codespaces

Current browser; stable broadband

8 GB system memory

Uses the GitHub account’s available Codespaces quota

Local installation

64-bit computer, 8 GB RAM, 4 GB free disk

16 GB RAM, 10 GB free disk

No course software fee

Tablets can read course pages, but a laptop or desktop is strongly recommended for notebook editing and assignments.

Supported Software Versions#

  • Python 3.12 is the reference interpreter used by the course build and Codespaces configuration.

  • Jupyter Book 1.0.4.post1 is pinned in requirements.txt.

  • Git 2.40 or newer is recommended only for local or Codespaces repository work.

  • The complete private student repository includes requirements.txt; use that file as the authoritative package list rather than following a public course-source repository or installing packages individually.

Rendered readings, slides, and narration require only a browser.

Google Colab Setup (Complete Private Student Repository)#

  1. In Populi, open the single private course repository assigned to you and confirm its name includes your GitHub username. You use this same repository for all eight modules.

  2. In Colab, choose File → Open notebook → GitHub, authorize access to your private repositories, select your assigned repository, and open modules/module-N/lab.ipynb for the current Populi module.

  3. Keep the default CPU runtime, choose Runtime → Run all, preserve the baseline evidence, make the required controlled change, and complete the exit-ticket fields.

  4. Choose File → Save a copy in GitHub, select the same private repository and branch, keep the module path, and enter a descriptive commit message. If institutional settings prevent direct Colab-to-GitHub saving, download the notebook and replace the matching file through GitHub or Codespaces, creating a commit there. A Drive-only copy is not submitted work.

  5. Open and complete modules/module-N/exercise.ipynb the same way, replace the prompts in MEMO.md with the required evidence memo, and complete SUBMISSION.md with the immutable commit URL and files-to-grade list. Upload SUBMISSION.md plus the requested memo or artifact in Populi.

If a GPU extension is assigned, choose Runtime → Change runtime type → T4 GPU when the free tier offers it. GPU availability is not guaranteed, so every required activity has a CPU path. Colab Pro is optional and is not a course requirement.

GitHub Codespaces Setup (Complete Private Student Repository)#

  1. Open the private course repository assigned in Populi and select Code → Codespaces → Create codespace on main. Create it once and reuse it for the course.

  2. Wait for dependency installation and the course Python kernel registration to finish.

  3. For the current module, open modules/module-N/lab.ipynb, run and complete it, then complete modules/module-N/exercise.ipynb, MEMO.md, and SUBMISSION.md. Select the course Python kernel when prompted.

  4. Save the graded module files, inspect the changes, commit with a descriptive message, and push to the private repository. Copy that immutable commit URL into SUBMISSION.md, then upload the completed record plus the requested memo or artifact in Populi. The record is an upload receipt and does not need to be part of the commit it identifies.

Use Codespaces when an activity needs multiple files, Git, tests, or a complete project. The Pages site is for reading; your student repository is your working environment.

Optional Local Installation#

git clone <your-assigned-student-repository-url>
cd <your-assigned-student-repository-folder>
python3.12 -m venv .venv
source .venv/bin/activate  # Windows PowerShell: .venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
pip install -r requirements.txt
jupyter lab

In JupyterLab, open the current modules/module-N/lab.ipynb and exercise.ipynb. Verify the installation with python --version, jupyter lab --version, and python -c "import numpy, matplotlib, torch".

Slides and RISE#

Students can read every slide deck as an ordinary web page from the course module map. Facilitators who want full-screen presentation mode should open modules/module-N/slides.ipynb in the configured Jupyter environment and start the RISE slideshow. The matching narration.md page is the prepared script for that deck.

Troubleshooting Checklist#

  • Confirm that you opened the correct module and selected the course Python kernel.

  • Restart the notebook runtime, then run cells from the top in order.

  • Do not install a paid service to solve an environment error; use the CPU/Colab path or ask the instructor.

  • When requesting help, include the module number, environment (Colab/Codespaces/local), exact error, and the cell where it occurred.