Detailed Exam Domain CoverageBefore diving into the course details, here is the exact breakdown of the AWS Certified Generative AI Developer – Professional exam domains to help you focus your study efforts:Domain 1: Foundation Model Integration, Data Management, and Compliance (31%)Integrate foundation models into applications and workflows.Design and manage data pipelines for GenAI solutions.Apply compliance, governance, and data security standards.Utilize vector stores and Retrieval Augmented Generation (RAG).Evaluate foundation models for quality and responsibility.Domain 2: Implementation and Integration (26%)Implement GenAI services using AWS Bedrock and related services.Develop and apply prompt engineering techniques.Build agentic AI solutions and orchestrate workflows.Integrate GenAI applications with AWS Lambda, API Gateway, and other services.Deploy and manage generative AI models in production.Domain 3: AI Safety, Security, and Governance (20%)Apply security controls and encryption for GenAI workloads.Implement responsible AI practices and risk assessments.Establish governance frameworks for model usage.Ensure data privacy and compliance with regulatory requirements.Monitor and audit AI system behavior for safety.Domain 4: Operational Efficiency and Optimization for GenAI Applications (12%)Optimize cost and performance of GenAI workloads.Scale inference using appropriate AWS compute options.Monitor application metrics with CloudWatch and logs.Implement caching and latency reduction strategies.Tune model parameters for operati
What you'll learn
Integrate foundation models into applications
Manage data pipelines for generative AI
Implement AWS Bedrock services
Apply security controls for AI workloads
Optimize performance of generative AI applications
Course objectives
Prepare for the AWS Certified Generative AI Developer exam
Develop skills in compliance and governance for AI
Learn how to deploy and manage generative AI models in production