Enterprise AI Monitoring and Optimization

This unit covers operationalizing, monitoring, and optimizing enterprise AI/ML systems in cloud environments, with hands-on use of monitoring templates, endpoint tracking, and platform evaluation tools. Students compare major AI/ML cloud service stacks (including Microsoft) and develop plans for model governance, performance tuning, and ongoing maintenance.

Learning Objectives

• Analyze and compare AI/ML cloud platform features and services to select an appropriate enterprise solution using an AI/ML platform evaluation sheet
• Apply templates and best practices to design and implement a model monitoring system that tracks endpoints, performance metrics, and drift using the model monitoring tracking sheet
• Demonstrate techniques to optimize model performance and inference efficiency, including tuning, scaling, and platform-specific deployment strategies
• Evaluate generative AI use cases and produce an operational plan that incorporates monitoring, governance, and remediation workflows using the generative AI use case planner