This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some courses have accessibility limitations and are working to address. If you require accommodation, please contact AWS Training and Certification Customer Support.
Learners will gain hands-on experience building a conversational protein research assistant using Amazon Bedrock AgentCore. The course covers parsing natural language queries into structured search parameters, deploying a custom ML model as a serverless endpoint, performing vector similarity search over protein embeddings with pgvector on Amazon Aurora PostgreSQL, and orchestrating multiple specialized tools -- including nested LLM agents -- within a single runtime. Participants will learn to create an end-to-end agent application that enables researchers to find structurally similar peptides and generate AI-powered scientific summaries through a conversational interface.
