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Duration 14 hours
Course Outline
Foundations of Interactive AI Agents
- Overview of AgentCore’s interactive features
- Creating enriched workflows using memory and tools
- Applications across analytics, automation, and support domains
Managing AgentCore Memory
- Establishing session persistence
- Structuring multi-step, context-aware processes
- Practical lab: Developing a data analysis agent with memory capabilities
Advanced Computation via Code Interpreter
- Review of supported operations and security protocols
- Safe execution of transformations and calculations
- Practical lab: Implementing real-time data adjustments
Live Engagement with the Browser Tool
- Configuring the browser tool within agent frameworks
- Fetching data and interacting with user interfaces
- Practical lab: Creating an agent with web interaction skills
Synthesizing Memory, Code, and Browser Capabilities
- Linking workflows across memory and various tools
- Architecting multi-modal, interactive experiences
- Practical lab: Building a customer support assistant
Validation and Observability
- Troubleshooting interactive processes
- Tracking and monitoring tool utilization
- Practical lab: Setting up observability dashboards for interactive agents
Enterprise Deployment Best Practices
- Striking a balance between interactivity, security, and governance
- Enhancing performance and user experience
- Reviewing enterprise adoption examples
Conclusion and Future Pathways
Requirements
- Proficiency in Python or JavaScript for rapid prototyping
- Comprehensive understanding of LLM-driven application architecture
- Knowledge of cloud-native data pipelines
Target Audience
- Machine Learning Engineers
- Data Scientists
- UX-Oriented Developers
