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 rich workflows leveraging memory and tools
- Exploring use cases across analytics, automation, and support
Working with AgentCore Memory
- Configuring session persistence
- Architecting multi-step, context-aware workflows
- Practical lab: Building a memory-enabled data analysis agent
Dynamic Computation with the Code Interpreter
- Reviewing supported operations and security constraints
- Safely executing transformations and calculations
- Practical lab: Enabling real-time data transformations
Real-Time Interaction with the Browser Tool
- Configuring the browser tool within agent workflows
- Managing data retrieval and user interface interactions
- Practical lab: Developing an agent with web interaction capabilities
Integrating Memory, Code, and Browser Tools
- Chaining workflows across memory and tools
- Designing multi-modal, interactive workflows
- Practical lab: Creating a customer support assistant
Testing and Observability
- Debugging complex interactive workflows
- Logging and monitoring tool utilisation
- Practical lab: Establishing observability dashboards for interactive agents
Best Practices for Enterprise Deployment
- Balancing interactivity with security and governance protocols
- Optimising performance and enhancing user experience
- Case studies on successful enterprise adoption
Summary and Next Steps
Requirements
- Practical experience with Python or JavaScript for prototyping
- A solid understanding of LLM-driven application design
- Familiarity with cloud-based data workflows
Target Audience
- ML engineers
- Data scientists
- UX-focused developers
14 Hours
