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Duration 14 hours
Course Outline
Foundations of Interactive AI Agents
- Overview of AgentCore’s interactive features
- Architecting complex workflows using memory and tools
- Applications across analytics, automation, and support domains
Implementing AgentCore Memory
- Setting up session persistence
- Structuring multi-step, context-aware processes
- Practical exercise: Creating a data analysis agent with memory capabilities
Dynamic Processing via the Code Interpreter
- Review of supported operations and security protocols
- Safely executing data transformations and calculations
- Practical exercise: Implementing real-time data processing
Real-Time Engagement with the Browser Tool
- Configuring the browser tool for agent integration
- Techniques for data extraction and UI interaction
- Practical exercise: Developing an agent with web browsing capabilities
Synergizing Memory, Code, and Browser Tools
- Sequencing workflows across memory and various tools
- Designing multi-modal, interactive user journeys
- Practical exercise: Building a customer support assistant
Testing and Observability Strategies
- Debugging complex interactive flows
- Tracking and monitoring tool utilization
- Practical exercise: Setting up observability dashboards for interactive agents
Enterprise Deployment Best Practices
- Harmonizing interactivity with security and governance standards
- Enhancing performance and user experience metrics
- Case studies on enterprise implementation
Conclusion and Path Forward
Requirements
- Proficiency in Python or JavaScript for prototyping
- Conceptual understanding of LLM-driven application architecture
- Experience with cloud-based data processing pipelines
Target Audience
- Machine Learning Engineers
- Data Scientists
- Developers with a focus on User Experience (UX)
