• Role of SAP AI Core in SAP Business Technology Platform
• AI Core vs AI Launchpad overview
• Business use cases for SAP AI services
• End-to-end AI lifecycle in SAP landscape
• Runtime, execution, and orchestration concepts
• Kubernetes-based infrastructure basics
• Integration with SAP AI Launchpad
• Architecture supports scalable AI workloads
• AI Core instance creation
• Resource groups and namespaces
• Authentication and service keys
• Environment setup enables AI execution
• Training pipelines and execution flows
• Model versioning and lifecycle control
• Artifact management concepts
• Workflow ensures repeatable AI operations
• Docker images and execution templates
• Handling datasets and input artifacts
• Monitoring training runs
• Training enables accurate models
• Serving endpoints and inference concepts
• Online vs batch inference
• Scaling and availability handling
• Deployment enables AI consumption
• Integration with SAP BTP services
• Using APIs for inference consumption
• Event-driven AI scenarios
• Integration embeds AI into business processes






















