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
Overview of Interactive AI Agents
- Summary of AgentCore’s interactive features
- Architecting complex workflows using memory and tools
- Practical applications in analytics, automation, and support
Implementing AgentCore Memory
- Setting up session persistence
- Building multi-step, context-sensitive workflows
- Lab exercise: Creating a memory-driven data analysis agent
Executing Dynamic Computation via Code Interpreter
- Reviewing supported operations and security limitations
- Safely performing transformations and calculations
- Lab exercise: Facilitating real-time data transformations
Real-Time Engagement via Browser Tool
- Configuring the browser tool within agent workflows
- Handling data retrieval and UI interactions
- Lab exercise: Developing an agent with web interaction features
Synthesizing Memory, Code, and Browser Tools
- Orchestrating workflows across memory and tool integrations
- Designing multi-modal, interactive experiences
- Lab exercise: Constructing a customer support assistant
Testing and Observability Strategies
- Debugging complex interactive workflows
- Implementing logging and monitoring for tool usage
- Lab exercise: Building observability dashboards for interactive agents
Enterprise Deployment Best Practices
- Striking a balance between interactivity, security, and governance
- Optimizing system performance and user experience
- Review of enterprise adoption case studies
Conclusion and Future Directions
Requirements
- Proficiency in Python or JavaScript for application prototyping
- A solid grasp of LLM-driven application architecture
- Experience with cloud-native data workflows
Target Audience
- Machine Learning Engineers
- Data Scientists
- UX-oriented Developers
