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 features
- Architecting sophisticated workflows using memory and tools
- Practical applications in analytics, automation, and support
Utilizing AgentCore Memory
- Setting up session persistence
- Creating multi-step, context-sensitive workflows
- Lab exercise: Developing a data analysis agent with memory capabilities
Performing Dynamic Computations via the Code Interpreter
- Review of supported operations and security limitations
- Safely executing data transformations and calculations
- Lab exercise: Implementing real-time data processing
Achieving Real-Time Engagement with the Browser Tool
- Configuring the browser tool within agent workflows
- Handling data retrieval and UI interactions
- Lab exercise: Constructing an agent with web browsing and interaction skills
Synthesizing Memory, Code, and Browser Tools
- Orchestrating workflows that link memory and tool usage
- Designing multi-modal, highly interactive processes
- Lab exercise: Building a comprehensive customer support assistant
Testing and Observability
- Diagnosing issues in interactive workflows
- Tracking and monitoring tool utilization
- Lab exercise: Creating observability dashboards for interactive agents
Best Practices for Enterprise Deployment
- Maintaining a balance between interactivity, security, and governance
- Enhancing performance and user experience
- Case studies on enterprise-level adoption
Conclusion and Recommended Next Steps
Requirements
- Proficiency in Python or JavaScript for prototype development
- Conceptual understanding of LLM-driven application design
- Working knowledge of cloud-based data workflows
Intended Audience
- ML engineers
- Data scientists
- UX-focused developers
14 Hours
