BAIABAAWAmazon Web ServicesAW-BAIABA1.0<p>In this course learners will:</p> <ul> <li>Define agentic AI characteristics and differentiate them from traditional AI systems.</li><li>Identify the core agent components and their interactions.</li><li>Describe how Bedrock AgentCore services support agentic AI.</li><li>Deploy agents by using supported frameworks with AgentCore Runtime.</li><li>Describe the core features of AgentCore Runtime.</li><li>Configure serverless execution with session isolation.</li><li>Configure AgentCore Identity for enterprise security requirements.</li><li>Create policies to secure agent tool calls using AgentCore Policy.</li><li>Implement secure token management and permission delegation.</li><li>Ensure compliance with data governance and audit requirements.</li><li>Implement different tool integration patterns, including built-in tools and protocol-based tools.</li><li>Design and deploy Model Context Protocol (MCP) servers and clients for extensible agent capabilities.</li><li>Describe common authentication patterns for agent tool use.</li><li>Configure AgentCore Gateway components for secure and authorized tool access.</li><li>Implement agentic memory patterns for different use cases.</li><li>Configure AgentCore Memory operations for context-aware development.</li><li>Optimize memory performance for production workloads.</li><li>Configure AgentCore Observability for production monitoring.</li><li>Implement Amazon CloudWatch integration and specialized tracing.</li><li>Describe the core features of AgentCore Evaluations.</li><li>Integrate agentic systems with production APIs and services.</li><li>Design deployment strategies for production environments.</li><li>Assess production readiness and establish continuous improvement processes</li></ul><p>We recommend that attendees of this course have:</p> <p><span class="cms-link-marked"><a class="fl-href-prod" href="/swisscom/fr/course/amazon-aaif"><svg role="img" aria-hidden="true" focusable="false" data-nosnippet class="cms-linkmark"><use xlink:href="/css/img/icnset-linkmarks.svg#linkmark"></use></svg>Agentic AI Foundations <span class="fl-prod-pcode">(AAIF)</span></a></span></p><ul> <li>Software developers seeking intermediate knowledge for building advanced agentic AI systems</li><li>Technical professionals exploring AI capabilities and interested in building advanced agentic AI systems.</li><li>Development teams building advanced agentic AI solutions.</li></ul><h5>Module 1: Foundations of Agentic AI Patterns</h5><ul> <li>Agent building blocks</li><li>Amazon Bedrock AgentCore introduction</li></ul><h5>Module 2: AgentCore Runtime and Framework Integration</h5><ul> <li>Supported frameworks and implementation</li><li>AgentCore Runtime overview</li><li>Infrastructure and deployment</li></ul><h5>Module 3: Security and Identity Management</h5><ul> <li>Security and identity management</li><li>Securing your agents with AgentCore Identity</li></ul><h5>Module 4: Tool Integration and AgentCore Gateway </h5><ul> <li>Amazon Bedrock AgentCore Policy</li><li>Built-in tools and custom integration</li><li>Model Context Protocol (MCP)</li><li>AgentCore Gateway</li><li>Implementing AgentCore Gateway</li><li>Amazon Bedrock AgentCore Policy</li></ul><h5>Module 5: Agentic Memory Implementation </h5><ul> <li>Agentic memory core concepts</li><li>AgentCore Memory</li><li>Securing AgentCore Memory</li></ul><p><strong>Hands-on Lab: Enhance and Scale Agents with Amazon Bedrock AgentCore</strong></p> <h5>Module 6: Production Monitoring and Observability </h5><ul> <li>Monitoring agents with AgentCore Observability</li><li>Verifying agent performance with AgentCore Evaluation</li></ul><h5>Module 7: Course Wrap-up</h5><ul> <li>Next steps and additional resources</li><li>Course summary</li></ul>In this course learners will: - 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 processesWe recommend that attendees of this course have: Agentic AI Foundations (AAIF)- Software developers seeking intermediate knowledge for building advanced agentic AI systems - Technical professionals exploring AI capabilities and interested in building advanced agentic AI systems. - Development teams building advanced agentic AI solutions.Module 1: Foundations of Agentic AI Patterns - Agent building blocks - Amazon Bedrock AgentCore introduction Module 2: AgentCore Runtime and Framework Integration - Supported frameworks and implementation - AgentCore Runtime overview - Infrastructure and deployment Module 3: Security and Identity Management - Security and identity management - Securing your agents with AgentCore Identity Module 4: Tool Integration and AgentCore Gateway - Amazon Bedrock AgentCore Policy - Built-in tools and custom integration - Model Context Protocol (MCP) - AgentCore Gateway - Implementing AgentCore Gateway - Amazon Bedrock AgentCore Policy Module 5: Agentic Memory Implementation - Agentic memory core concepts - AgentCore Memory - Securing AgentCore Memory Hands-on Lab: Enhance and Scale Agents with Amazon Bedrock AgentCore Module 6: Production Monitoring and Observability - Monitoring agents with AgentCore Observability - Verifying agent performance with AgentCore Evaluation Module 7: Course Wrap-up - Next steps and additional resources - Course summary1 jour750.00695.00960.00900.00590.00750.00750.00750.00750.00750.00