MACHINE LEARNING OPERATIONS

Catalog description

This capstone course bridges the gap between theoretical machine learning and real-world application. Students will learn the principles, tools, and best practices for deploying, managing, and scaling machine learning models in production environments. The course covers the entire MLOps lifecycle, including data engineering, automated pipelines, model deployment, monitoring, and governance. A significant portion of the course is dedicated to a semester-long capstone project where student teams build, deploy, and maintain an end-to-end ML system. PREREQ: COMPSCI 432 AND COMPSCI 468