Building Agentic AI with Amazon Bedrock AgentCore

In this course, you will learn to: • Define agentic AI characteristics and differentiate them from traditional AI systems. • Identify the core agent components and their interactions. • Describe how Bedrock AgentCore services support agentic AI. • Deploy agents by using supported frameworks with AgentCore Runtime. • Describe the core features of AgentCore Runtime. • Configure serverless execution with session isolation. • Configure AgentCore Identity for enterprise security requirements. • Create policies to secure agent tool calls using AgentCore Policy. • Implement secure token management and permission delegation. • Ensure compliance with data governance and audit requirements. • Implement different tool integration patterns, including built-in tools and protocol-based tools. • Design and deploy Model Context Protocol (MCP) servers and clients for extensible agent capabilities. • Describe common authentication patterns for agent tool use. • Configure AgentCore Gateway components for secure and authorized tool access. • Implement agentic memory patterns for different use cases. • Configure AgentCore Memory operations for context-aware development. • Optimize memory performance for production workloads. • Configure AgentCore Observability for production monitoring. • Implement Amazon CloudWatch integration and specialized tracing. • Describe the core features of AgentCore Evaluations. • Integrate agentic systems with production APIs and services. • Design deployment strategies for production environments. • Assess production readiness and establish continuous improvement processes

Intended audience • Software developers seeking intermediate knowledge for building agentic systems • Technical professionals exploring AI capabilities and interested in building agentic AI systems. • Development teams building agentic AI solutions. Prerequisites We recommend that attendees of this course have: • Agentic AI Foundations