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.
Duration 14 hours
Course Outline
Introduction to Interactive AI Agents
- Overview of AgentCore's interactive capabilities
- Designing comprehensive workflows utilizing memory and tools
- Exploring use cases in analytics, automation, and support
Managing State with AgentCore Memory
- Configuring session persistence
- Developing multi-step, context-aware workflows
- Practical lab: Creating a data analysis agent with memory capabilities
Dynamic Computation Using the Code Interpreter
- Reviewing supported operations and security constraints
- Safe execution of transformations and calculations
- Practical lab: Implementing real-time data transformations
Real-Time Interaction via the Browser Tool
- Setting up the browser tool for agent workflows
- Managing data retrieval and user interface interactions
- Practical lab: Building an agent with web interaction features
Integrating Memory, Code, and Browser Tools
- Chaining workflows across memory and various tools
- Designing multi-modal, interactive workflows
- Practical lab: Developing a customer support assistant
Testing and Observability
- Debugging interactive workflows
- Logging and monitoring tool utilization
- Practical lab: Creating observability dashboards for interactive agents
Best Practices for Enterprise Deployment
- Striking a balance between interactivity, security, and governance
- Optimizing for performance and user experience
- Examining enterprise adoption case studies
Summary and Next Steps
Requirements
- Practical experience with Python or JavaScript for prototyping purposes
- A solid grasp of application design powered by large language models (LLMs)
- Familiarity with cloud-based data processing workflows
Target Audience
- Machine Learning engineers
- Data scientists
- Developers with a focus on user experience (UX)
