# Phase 1: Math Foundations

> The intuition behind every AI algorithm, through code, not textbooks.

## Start this phase on GitHub

**Prerequisites:** Complete Phase 0, or confirm that Python 3.11+ and Git work
from the repository root.

**First lesson:** [Linear Algebra Intuition](01-linear-algebra-intuition/)

Run this command from the repository root:

```bash
python3 phases/01-math-foundations/01-linear-algebra-intuition/code/vectors.py
```

Keep the command, exit code, normalized-vector output, projection residual,
and one sentence explaining why a matrix-vector product is a neural-network
layer.

**Next action:** Change one input vector, predict the result, run it again,
then continue to [Vectors, Matrices and Operations](02-vectors-matrices-operations/).

Browse the [full Phase 1 lesson list](../../README.md#phase-1) or the
[cross-phase roadmap](../../ROADMAP.md).
