Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Interactive AI Agents
- Overview of AgentCore’s interactive capabilities
- Designing sophisticated workflows utilizing memory and tools
- Applicable use cases in analytics, automation, and support functions
Working with AgentCore Memory
- Configuration of session persistence
- Architecting multi-step, context-aware workflows
- Practical lab: Constructing a memory-enabled data analysis agent
Dynamic Computation with the Code Interpreter
- Reviewing supported operations and security limitations
- Safely executing transformations and calculations
- Practical lab: Enabling real-time data transformations
Real-Time Interaction with the Browser Tool
- Configuring the browser tool for agent-based workflows
- Managing data retrieval and user interface engagements
- Practical lab: Developing an agent with web interaction features
Integrating Memory, Code, and Browser Tools
- Linking workflows across memory systems and tools
- Designing multi-modal, interactive experiences
- Practical lab: Building a customer support assistant
Testing and Observability
- Debugging interactive workflow processes
- Logging and monitoring tool utilization
- Practical lab: Implementing observability dashboards for interactive agents
Best Practices for Enterprise Deployment
- Striking a balance between interactivity, security, and governance
- Optimizing systems for performance and user experience
- Review of enterprise adoption case studies
Summary and Next Steps
Requirements
- Practical experience with Python or JavaScript for prototyping applications
- A solid understanding of LLM-driven application architecture
- Familiarity with cloud-based data processing workflows
Target Audience
- ML Engineers
- Data Scientists
- UX-focused Developers
14 Hours
