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Duration 14 hours
Course Outline
Introduction to LLM Agents and AutoGen Studio
- What defines multi-agent systems?
- An overview of AutoGen and AutoGen Studio
- Exploring the visual design interface
Planning Agent-Based Workflows
- Identifying business use cases for agent collaboration
- Aligning user goals with agent interactions
- Structuring task flows and triggers
Creating and Configuring Agents
- Assigning roles and behaviors to agents
- Crafting effective prompts and objectives
- Utilizing predefined versus custom agent templates
Managing Multi-Agent Communication
- Structuring message passing and coordination
- Regulating agent turn-taking and logic paths
- Establishing agent groups and dependencies
Error Handling and Response Management
- Managing missing inputs and implementing fallbacks
- Recording and analyzing conversation flows
- Refining logic based on agent feedback
No-Code Deployment and Testing
- Executing workflows within AutoGen Studio
- Debugging using visual execution history
- Modifying workflows based on testing outcomes
Real-World Use Cases and Best Practices
- Internal workflow automation (e.g., summarization, approvals)
- Developing product prototypes with AI logic
- Strategies for scalable and reusable agent design
Summary and Next Steps
Requirements
- Familiarity with AI or automation concepts
- Confidence in using visual tools and process modeling
- No prior coding experience is necessary
Target Audience
- Product managers
- Business analysts
- Innovation teams and non-coders
Testimonials (1)
I liked that he constantly provided examples but also offered time for individual work on what he presented.
