Get Started

Download the latest installer from python.org, open the .pkg file and click through the installer.

Prefer the terminal? If you have Homebrew installed, run:

brew install python

Then open a new terminal window and confirm it works:

python3 --version

You should see something like Python 3.12.x.

Download and install Visual Studio Code from code.visualstudio.com. It's the editor we'll use to open and run the challenge notebook.

Open VS Code, click the Extensions icon in the left sidebar (or press Cmd+Shift+X) and install:

• Python ms-python.python
  Language support, debugging and environment selection.
• Jupyter ms-toolsai.jupyter
  Run and edit .ipynb notebooks directly inside VS Code.
• Pylance ms-python.vscode-pylance
  Fast autocompletion and type checking (ships with Python).

Open the challenge you want to tackle and click Download Starter Kit. Unzip it, then open the folder in VS Code via File → Open Folder…

The kit contains the challenge notebook (a .ipynb file) and the dataset. If it includes a requirements.txt, you'll use it in step 6.

A virtual environment (“venv”) keeps each challenge's libraries isolated from the rest of your system. Open the built-in terminal in VS Code (Terminal → New Terminal) and run, from inside the challenge folder:

python3 -m venv .venv

Then activate it:

source .venv/bin/activate

When it's active you'll see (.venv) at the start of your terminal prompt.

If the starter kit includes a requirements.txt, install everything at once:

pip install -r requirements.txt

Otherwise, install the standard data-science toolkit our challenges rely on:

pip install jupyter pandas numpy scikit-learn matplotlib

Open the .ipynb file in VS Code. In the top-right corner click Select Kernel and choose the .venv environment you just created.

Now run a cell with Shift+Enter, or use Run All at the top to execute the whole notebook. That's it — you're ready to experiment and submit your results to the leaderboard.