AIP-C01 study notes
- Foundation model integration, data and compliance AIP-C01 notes on solution design, choosing and configuring foundation models, resilient model access, data pipelines for FMs, vector stores, retrieval, embeddings, chunking and prompt engineering and governance. 31%
- Implementation and integration AIP-C01 notes on agents and tool use, MCP, Strands and Agent Squad, deployment options for models, enterprise integration, FM API patterns, streaming, routing and developer tooling. 26%
- AI safety, security and governance AIP-C01 notes on Bedrock Guardrails, hallucination control, defence in depth, prompt injection, network and data security, privacy and PII, governance, auditability and responsible AI. 20%
- Operational efficiency and optimization AIP-C01 notes on token efficiency, model selection for cost, throughput and capacity, caching, latency, retrieval tuning, inference parameters and observability for GenAI applications. 12%
- Testing, validation and troubleshooting AIP-C01 notes on evaluating GenAI output quality, Bedrock model evaluation, LLM-as-a-judge, RAG and agent evaluation, deployment validation and troubleshooting content, API, prompt and retrieval problems. 11%