Course Outline:
Module 1: Advanced Agent Architectures
- Overview of autonomous agents
- Agent design patterns and architectures
- Architectures: Reflex, Deliberative, Hybrid
- Planning systems and decision-making
- Advanced memory architectures
- State management and persistence
- LangChain, CrewAI, AutoGen frameworks
Module 2: Building Agent Infrastructure
- Setting up a development environment
- Installing necessary libraries (LangChain, AutoGen, ChromaDB, etc.)
- Connecting AI Agents to APIs and knowledge bases
- Implementing agent framework from scratch
- Creating custom tools and capabilities
- Advanced prompt engineering techniques
Module 3: Advanced Memory Systems
- Vector database implementation
- Long-term and working memory
- Context window management
- Hierarchical memory structures
Module 4: Tool Integration and API Development
- Creating custom tools
- API integration patterns
- Function calling and tool use
- Error handling and recovery
Module 5: Multi-Agent Systems
- Agent communication protocols
- Implementing agent cooperation
- Task distribution and management
- Conflict resolution
Module 6: Project Implementation
- Building a complete agent system
- Testing and evaluation
- Performance optimization
- Deployment considerations
Module 7: Best Practices and Future Directions
- Security considerations
- Scaling agent systems
- Latest research and trends
- Resources for continued learning
Optional: Hands-on Project
- Building a task management agent
- Implementing a research assistant
- Creating a multi-agent system
Training material provided: Yes (Digital format)
