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Duration 14 hours
Course Outline
Introduction to LLM Agents and AutoGen Studio
- Defining multi-agent systems
- Overview of AutoGen and AutoGen Studio
- Exploring the visual design interface
Planning Agent-Based Workflows
- Identifying business use cases suitable for agent collaboration
- Aligning user goals with agent interactions
- Designing task flows and triggers
Creating and Configuring Agents
- Assigning specific roles and behaviors to agents
- Crafting effective prompts and objectives
- Leveraging predefined versus custom agent templates
Managing Multi-Agent Communication
- Structuring message passing and coordination mechanisms
- Controlling agent turn-taking and logical pathways
- Establishing agent groups and dependencies
Error Handling and Response Management
- Addressing missing inputs and implementing fallback strategies
- Logging and analyzing conversation flows
- Refining logic based on agent feedback
No-Code Deployment and Testing
- Executing workflows within AutoGen Studio
- Debugging through visual execution history
- Optimizing workflows based on test outcomes
Real-World Use Cases and Best Practices
- Automating internal workflows (e.g., summarization, approval processes)
- Developing product prototypes with AI logic
- Strategies for scalable and reusable agent design
Summary and Next Steps
Requirements
- A foundational understanding of AI or automation concepts
- Proficiency with visual tools and process modeling
- No prior coding experience 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.
