AWS Certified Generative AI Developer - Professional
--> Agentic Systems, Deployment, and Enterprise Integration
--> --> Module 4: Agent Safety, Control, and Human-in-the-Loop
--> --> Module 8: Developer Experience, Observability, and Troubleshooting
--> --> Module 7: Enterprise Integration, Security, and Compliance
--> --> Module 6: FM API Integration and Real-Time Delivery
--> --> Module 5: Model Deployment and Serving
--> --> Module 3: Multi-Agent Systems and Model Coordination
--> --> Module 2: Tools, Function Calling, and MCP
--> --> Module 1: Agent Fundamentals: Loops, Reasoning, Memory, and State
--> --> Module 0: The Agent Platform Landscape
--> Safety, Security, Privacy, Governance, and Responsible AI
--> --> Module 3: Output Safety and Deterministic Transformation
--> --> Module 8: Responsible AI: Transparency, Fairness, and Policy
--> --> Module 6: Privacy and PII Handling
--> --> Module 5: Data Security and Network Isolation
--> --> Module 1: The GenAI Threat Model
--> --> Module 2: Input Safety and Adversarial Defense
--> --> Module 4: Grounding, Verification, and Hallucination Control
--> --> Module 7: Governance, Lineage, and Auditability
--> Foundation Model Integration, Data Management, and Compliance
--> --> Module 7: Resilience, Customization, and Lifecycle
--> --> Module 6: Prompt Engineering and Governance
--> --> Module 5: Retrieval Mechanisms
--> --> Module 4: Vector Store Design
--> --> Foundation Model Integration, Data Management, and Compliance: Services
--> --> Module 3: Data Validation and Processing Pipelines
--> --> Module 2: Requirements elicitation for generative AI
--> AIP: Services Estate
--> --> AWS Storage
--> --> Developer Tools, Migration, and Customer Engagement
--> --> AWS Analytics
--> --> AWS Databases
--> --> Compute and Containers
--> --> AWS Networking
--> --> Management and Governance
--> --> Security, Identity, and Compliance
--> --> Amazon Q and Amazon Quick
--> --> Application Integration
--> --> The Purpose-Built AI Services
--> --> The SageMaker Family
--> --> The Bedrock Family
--> AWS Generative AI By Layer
--> --> Behavior Change Management
--> --> Source & Ingestion
--> --> Change Management & Governance
--> --> Tenancy, Quotas & Metering
--> --> Evaluation & Feedback
--> --> Cost & Capacity
--> --> Observability
--> --> Transport & Client
--> --> Identity & Entitlement
--> --> Orchestration & Control
--> --> Safety & Policy
--> --> State & Memory
--> --> Retrieval & Grounding
--> --> Model Invocation
--> --> Model Serving
--> --> Model Customization
--> --> Segmentation, Vectorization & Index Maintenance
--> --> Extraction, Sanitization & Normalization
--> Evaluation, Quality Assurance, and Troubleshooting
--> --> Module 4: RAG and Retrieval Evaluation
--> --> Module 9: Prompt and Retrieval Troubleshooting
--> --> Module 8: Systematic Troubleshooting: Content and Integration
--> --> Module 6: Human Feedback and Annotation
--> --> Module 1: Evaluation Foundations
--> --> Module 2: Evaluation Datasets and Ground Truth
--> --> Module 5: Agent Evaluation
--> --> Module 3: Automated Evaluation and Model Comparison
--> --> Module 7: Continuous Evaluation, Quality Gates, and Reporting
--> Cost Optimization, Performance, and Observability
--> --> Module 6: Latency Optimization and Inference Tuning
--> --> Module 8: Observability, Monitoring, and Troubleshooting
--> --> Module 7: Retrieval and Vector Store Performance
--> --> Module 5: Throughput, Capacity, and Scaling
--> --> Module 4: Caching
--> --> Module 3: Model Selection, Tiering, and Distillation
--> --> Module 2: Token Efficiency and Context Optimization
--> --> Module 1: The Token Economy