Tutorials¶

A step-by-step guided path from zero to a running MLOps pipeline on Snowflake.

Follow the tutorials in order the first time through. Each tutorial assumes you have completed the previous one.

#	Tutorial	What you will do
1	Prerequisites & Bootstrap	Install tooling, configure Snowflake access, bootstrap platform infrastructure.
2	Repo Mental Model	Understand the hub-spoke layout, component boundaries, and how code is organised.
3	Seed Shared Data	Generate and load mock PUDO data into the shared Snowflake schema.
4	Deploy Schema & Feature Store	Create the project schema, entities, and feature views.
5	Deploy & Run Training	Deploy the training DAG, generate datasets, train an XGBoost model, and register it.
6	Deploy & Run Inference	Deploy the inference DAG and run batch predictions.
7	Simulate, Evaluate & Alert	Simulate daily data cycles, evaluate predictions, and trigger alerts.
8	Change Promotion & ML Lifecycle	Understand how Git changes map to Snowflake ML lifecycle stages.

Before you start¶

Make sure you have read: