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Duration 14 hours
Course Outline
Introduction to LLM Agents and AutoGen Studio
- The concept of multi-agent systems
- Overview of AutoGen and AutoGen Studio
- Exploring the visual design interface
Planning Agent-Based Workflows
- Identifying business scenarios for agent collaboration
- Aligning user objectives with agent interactions
- Designing task sequences and triggers
Creating and Configuring Agents
- Defining agent roles and behaviors
- Crafting effective prompts and goals
- Utilizing predefined versus custom agent templates
Managing Multi-Agent Communication
- Architecting message passing and coordination
- Regulating agent turn-taking and logical paths
- Establishing agent groups and dependencies
Error Handling and Response Management
- Addressing missing inputs and implementing fallbacks
- Recording and analyzing conversation flows
- Optimizing logic based on agent feedback
No-Code Deployment and Testing
- Executing workflows within AutoGen Studio
- Troubleshooting using visual execution logs
- Refining workflows based on testing outcomes
Real-World Use Cases and Best Practices
- Automating internal processes (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 principles
- Proficiency with visual tools and process modeling
- No prior coding background is necessary
Target Audience
- Product managers
- Business analysts
- Innovation teams and non-developers
Testimonials (1)
I liked that he constantly provided examples but also offered time for individual work on what he presented.
