Guarding AI Performance: Metrics and Pipelines for Drift Detection

A practical guide to monitor AI systems for drift, design metric‑driven pipelines, set thresholds and alerts, evaluate champion models, and plan retraining and rollback to sustain trustworthy performance.

After completing this Pathway, you will be able to:

• Diagnose data drift and concept drift using appropriate metrics and cohorts
• Design monitoring pipelines with thresholds, alerts, approvals, and rollback readiness