Validating and Safeguarding Production AI

This long course focuses on the operational lifecycle of agentic AI systems: robust partitioning and dataset management, automated retraining pipelines, continuous monitoring for drift and anomalies, testing and secure deployment, and performance optimization of code and pipelines. You will practice partitioning strategies (time-series and stratified), monitoring and drift detection metrics (PSI and KS), and build CI/CD notebooks and automated workflows for model retraining and re-deployment using tools like MLflow and GitHub Actions. The course addresses software-engineering best practices—cl…