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1 · Classical ML in one week

The classical machine-learning vocabulary an AI engineer actually needs — features, splits, overfitting, the eight algorithms you'll see in real code, and an evaluation loop you can trust. Not a degree; the working shape.

After this track you can read a scikit-learn or XGBoost codebase without hunting terms, name why a model is over- or under-fitting, and set up a train/val/test split that isn't lying to you.

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