MLOps 106 – Scaling AI Workloads

(Weeks 11–12 | Lec 6 Hrs / Lab 18 Hrs / Ext 0 Hrs | 24 Total Hrs | 1.0 Credit Hrs)
Students will:

• Scale training and inference across cloud and edge
• Optimize compute, memory, and network resources
• Implement batch and streaming pipelines
• Manage cost-efficient scaling strategies

Prerequisite: MLOps 105 – Monitoring, Drift & Feedback Loops
Tools: AWS SageMaker, Azure ML, Google Vertex AI