At Course Completion

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