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Duration 14 hours
Course Outline
Introduction to LLM Agents and AutoGen Studio
- The concept of multi-agent systems
- An overview of AutoGen and AutoGen Studio
- Navigating the visual design interface
Planning Agent-Based Workflows
- Identifying business scenarios for agent collaboration
- Aligning user objectives with agent interactions
- Structuring task flows and triggers
Creating and Configuring Agents
- Defining agent roles and behaviors
- Crafting effective prompts and goals
- Leveraging predefined versus custom agent templates
Managing Multi-Agent Communication
- Designing message passing and coordination
- Regulating agent turn-taking and logical paths
- Forming agent groups and dependencies
Error Handling and Response Management
- Managing missing inputs and fallback scenarios
- Logging and analyzing conversation flows
- Refining logic based on agent feedback
No-Code Deployment and Testing
- Executing workflows in AutoGen Studio
- Debugging via visual execution history
- Optimizing workflows based on test outcomes
Real-World Use Cases and Best Practices
- Automating internal workflows (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
- Experience with visual tools and process modeling
- No prior coding experience is necessary
Target Audience
- Product managers
- Business analysts
- Innovation teams and non-technical roles
Testimonials (1)
I liked that he constantly provided examples but also offered time for individual work on what he presented.
