Deployment & Orchestration

Endpoints, agents, pipelines, and infrastructure as code

• Serving Predictions: Endpoints and Batch — The first fork every deployment question takes — real-time or batch — then endpoint anatomy, multi-model and multi-container serving, auto scaling, and instance selection. (4 lessons, 55 min)
• Deploying FMs, RAG, and Agents — Hosting foundation models — Bedrock, Custom Model Import, SageMaker — configuring Knowledge Bases and retrieval pipelines, and running agents with tools, state, and GPU scale. (4 lessons, 60 min)
• Provisioning ML Infrastructure as Code — CloudFormation and the CDK for ML stacks, containers for ML workloads on ECR/ECS/EKS, endpoints inside VPCs, and programmatic deployment with the SDK, CLI, and Boto3. (4 lessons, 50 min)
• MLOps Pipelines: CI/CD for Models — The Code* family building model pipelines, deployment strategies with rollback, Model Registry and MLflow versioning, prompt management, retraining triggers, and KB refresh. (4 lessons, 60 min)