01Module 4 - Model Registry and LifecycleMaster the model registry - the system that brings order, traceability, and governance to every model your team ships to production.02Model Registry ConceptsUnderstand what a model registry is, why it exists, and how it brings order to the chaos of managing ML models in production.03MLflow Model Registry in ProductionLearn how to use the MLflow Model Registry to manage model versions, stages, approval workflows, and webhooks for production ML teams.04Model Versioning StrategiesDesign versioning schemes for ML models that support safe rollbacks, A/B testing, champion/challenger management, and backward compatibility.05Model Staging and PromotionHow to safely gate model promotion through staging, production, and archiving with automated checks and human approval workflows.06Model Cards and DocumentationHow to write, automate, and maintain model cards that document model capabilities, limitations, training data, fairness evaluations, and regulatory compliance.07Model Rollback StrategiesDesigning fast, reliable model rollback procedures for when production models degrade - covering registry-based rollback, infrastructure rollback, and automated rollback controllers.
