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Course Outline

Introduction to Interactive AI Agents

  • Overview of AgentCore’s interactive capabilities
  • Designing robust workflows using memory and tools
  • Application scenarios in analytics, automation, and support

Managing AgentCore Memory

  • Configuring session persistence
  • Crafting multi-step, context-aware workflows
  • Hands-on lab: Developing a data analysis agent with memory capabilities

Dynamic Computation via the Code Interpreter

  • Supported operations and security constraints
  • Safely executing transformations and calculations
  • Hands-on lab: Implementing real-time data transformations

Real-Time Interaction using the Browser Tool

  • Setup of the browser tool for agent workflows
  • Techniques for data retrieval and user interface interaction
  • Hands-on lab: Creating an agent with web interaction features

Synthesizing Memory, Code, and Browser Tools

  • Linking workflows across memory and various tools
  • Designing multi-modal, interactive workflows
  • Hands-on lab: Building a customer support assistant

Testing and Observability

  • Debugging interactive workflows
  • Logging and monitoring tool utilization
  • Hands-on lab: Creating observability dashboards for interactive agents

Best Practices for Enterprise Deployment

  • Balancing interactivity with security and governance
  • Optimizing for performance and user experience
  • Enterprise adoption case studies

Summary and Next Steps

Requirements

  • Experience with Python or JavaScript for prototyping
  • Understanding of LLM-powered application design
  • Familiarity with cloud-based data workflows

Target Audience

  • ML engineers
  • Data scientists
  • UX-focused developers
 14 Hours

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Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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