AIP-C01: AWS Certified Generative AI Developer - Professional

In this track, learn to design generative AI solutions on AWS by analyzing requirements, selecting and customizing foundation models, implementing data pipelines, configuring vector stores for RAG, designing retrieval mechanisms, and applying prompt engineering strategies with governance for reliable FM interactions.

In this track, learn to build agentic AI solutions with memory and tool integrations, implement multi-agent orchestration, deploy foundation models at scale, design enterprise integration architectures with hybrid connectivity, and implement resilient FM API integrations with application patterns for business workflows.

In this track, learn to implement input/output safety controls and guardrails, reduce hallucinations and defend against adversarial attacks, apply data security and privacy controls for protected GenAI environments, and establish AI governance, compliance mechanisms, and responsible AI principles.

In this track, learn to optimize GenAI workloads through token efficiency, caching, and cost management strategies. Enhance application performance and throughput capacity while implementing comprehensive monitoring systems and operational diagnostics for production generative AI applications.

In this track, learn to implement evaluation frameworks for GenAI systems including model assessment and continuous quality assurance. Validate RAG pipelines, agents, and deployments while developing skills to troubleshoot prompting, retrieval, API, and workflow failures effectively.