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Course Outline
Overview of Interactive AI Agents
- Examination of AgentCore's interactive capabilities
- Architecting robust workflows using memory and tools
- Applications in analytics, automation, and support environments
Managing AgentCore Memory
- Setting up session persistence
- Creating multi-step, context-aware workflows
- Practical session: developing a data analysis agent with memory capabilities
Dynamic Processing via Code Interpreter
- Review of supported operations and security limitations
- Safe execution of transformations and calculations
- Practical session: implementing real-time data processing
Live Interaction via Browser Tool
- Configuration of the browser tool within agent workflows
- Handling data retrieval and user interface interactions
- Practical session: creating an agent with web navigation abilities
Synthesizing Memory, Code, and Browser Tools
- Connecting workflows across memory modules and external tools
- Designing multi-modal, interactive user journeys
- Practical session: building a comprehensive customer support assistant
Verification and Monitoring
- Troubleshooting interactive workflows
- Logging and monitoring tool utilization
- Practical session: setting up observability dashboards for interactive agents
Enterprise Deployment Standards
- Aligning interactivity with security protocols and governance
- Enhancing performance and user experience
- Case studies on enterprise-level adoption
Conclusion and Future Pathways
Requirements
- Proficiency in Python or JavaScript for prototyping
- Conceptual understanding of LLM-powered application architecture
- Familiarity with cloud-based data processing workflows
Target Audience
- ML engineers
- Data scientists
- UX-focused developers
14 Hours
