Python Environment Installation

Please follow these steps to install the software for Python for the Data Science and Tutorial courses.

Step 1. Create a GitHub account

Skip this step if you already have a GitHub account.

https://github.com/signup

Step 2. Apply for GitHub Education benefits

https://github.com/settings/education/benefits

Approval can take a few days, so apply now and continue with the next steps in the meantime. Once you are approved, you can activate GitHub Copilot for free (Step 10).

Step 3. Download and install VS Code

https://code.visualstudio.com/download

Step 4. Start VS Code and install the extensions

Open the Extensions tab on the left (menu: View | Extensions, shortcut ⇧⌘X on Mac, Ctrl+Shift+X on Windows).

Search for and install these extensions:

• Python
• Jupyter
• GitHub Copilot Chat (you will sign in to Copilot in Step 10)

Optional: instead of GitHub Copilot, you can use a coding assistant you already pay for:

• If you have a ChatGPT Plus (or higher) plan, install Codex – OpenAI's coding agent.
• If you have a Claude Pro or Max subscription, install Claude Code for VS Code.

Step 5. Create and open a project folder

• In the menu: File | Open Folder…
• Navigate to where you want to create the folder
• Click New Folder and give it a name, e.g. bipm
• Click Open

Step 6. Open a terminal and install uv

In the menu: Terminal | New Terminal. Copy the command for your system into the terminal and press Return.

On a Mac:

curl -LsSf https://astral.sh/uv/install.sh | sh

On Windows:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Important: close the terminal (trash icon in the terminal panel) and open a new one (Terminal | New Terminal). Only new terminals know the uv command. Check that it works:

uv --version

Step 7. Install Python and the Python packages

Run these commands one by one in the terminal (inside your project folder).

uv init --python 3.13

This creates the project files (pyproject.toml, .python-version, main.py). Keep Python 3.13: TensorFlow does not support Python 3.14 yet.

uv add jupyter matplotlib seaborn pandas scipy pingouin statsmodels openpyxl statannotations scikit-learn xgboost shap numpy tensorflow lime treeinterpreter dtreeviz rfpimp

This downloads about 1 GB (mostly TensorFlow) and can take a few minutes. It creates a .venv folder that contains Python and all packages.

If VS Code asks whether to select the new environment for the workspace folder, click Yes.

Later, for example on a new computer or after cloning a project, uv sync reinstalls everything listed in pyproject.toml.

Step 8. Check the installation

uv run python -c "import pandas, sklearn, tensorflow, shap; print('All good')"

You should see All good (TensorFlow may print a few informational messages first).

Step 9. Use the environment in a Jupyter notebook

• In the menu: File | New File… and choose Jupyter Notebook
• Click Select Kernel (top right) → Python Environments… → .venv
• In the first cell, type the code below and run it (Shift+Return):

import pandas as pd
pd.__version__

If a version number appears, everything works. In every new notebook, check that .venv is selected as the kernel (top right).

Step 10. Activate GitHub Copilot

After your education benefits are approved (Step 2):

https://github.com/settings/copilot/features

Then sign in to GitHub in VS Code: click the Accounts icon (bottom left) and choose Sign in with GitHub to use GitHub Copilot.