AWS GenAI: RAG, AI Agents and Responsible AI

About this course

Deploying generative AI applications reliably, ethically, and at enterprise scale is a significant challenge. This course provides the advanced AWS architecture skills and responsible AI governance frameworks needed to implement trusted systems. You will master the production toolkit for foundation models on AWS, including model selection, Amazon Bedrock configurations, Retrieval-Augmented Generation (RAG) with vector databases, multi-step AI agents, prompt engineering, fine-tuning decision frameworks, and LLM benchmarking. A comprehensive responsible AI module addresses bias mitigation, dataset curation, explainability, legal risk management, and human-centered design through workplace role-play scenarios using AWS tools. The course concludes with a Python capstone project: building a production-ready Multimodal AI Knowledge Assistant that integrates text/image generation, function calling, a RAG pipeline, structured outputs, content moderation, and a documented governance layer. This course is designed for ML engineers, cloud architects, data scientists, and AI governance professionals with OpenAI API experience ready to deploy and govern enterprise AI systems on AWS.