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課程簡介
Introduction to CrewAI and Multi-Agent Architecture
- Overview of CrewAI concepts and architecture
- Understanding agent roles and flows
- Use cases and design patterns
Designing Custom Agents and Tools
- Defining agent goals, memory, and behavior
- Creating and integrating custom tools
- Tool abstraction and modular design
Advanced Agent Collaboration
- Sequencing and synchronization of tasks
- Nested and parallel flows
- Multi-agent decision making
API and System Integration
- Calling external APIs from agents
- Incorporating real-time data sources
- Building pipelines and dynamic inputs
Event-Driven Orchestration
- Trigger-based workflows and custom events
- Error handling and fallback logic
- Using webhooks and schedulers
Monitoring, Testing, and Optimization
- Observing agent behavior and performance
- Debugging workflows and logging
- Scaling strategies and optimization tips
Practical Implementation and Case Studies
- Implementing a domain-specific use case
- Case study: enterprise automation with CrewAI
- Lessons learned and best practices
Summary and Next Steps
最低要求
- 具備Python編程經驗
- 了解AI與機器學習基礎知識
- 熟悉API整合與軟體架構概念
目標受眾
- AI工程師
- 研究人員
- 軟體架構師
14 時間：
