Production & Professional Practice

A model that works in a notebook is an experiment; a model other people depend on is a product, and this domain covers the distance between the two. Production ML & MLOps is the operational half: tracking experiments so results can be reproduced, packaging and serving models as services, watching latency and drift, and the newer LLMOps playbook for generative systems — practised on real MLflow and real cases. ML Leadership & Product is the human half: what a model can honestly promise, how to read an evaluation without being fooled, and the questions that expose a shaky project before it ships.

Engineers will want the serving and monitoring labs; leaders and stakeholders can go straight to the literacy track, which assumes no code at all.