Advanced Agent Architectures & Multi-Agent Systems
This program deep dives into complex agent frameworks (e.g., LangChain, AutoGen), designing sophisticated multi-agent collaborative systems, agent evaluation, and debugging advanced agent behaviors.
Pre-Requisite
- Agent Memory & State Management
- Tool Integration for AI Agents, or significant experience building and deploying AI agents.
Course Outline
- 5 Sections
- 19 Lessons
- 5 Days
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- DAY 1 - Introduction to Advanced Agent Frameworks4
- 1.1Overview of popular Agentic AI frameworks (e.g., LangChain, AutoGen, CrewAI)
- 1.2Choosing the Right Framework for Different Use Cases
- 1.3Understanding Framework Components (Chains, Agents, Tools, Prompts, Memory)
- 1.4Hands-on: Getting started with a selected framework (e.g., LangChain basics, setting up an initial agent).
- DAY 2 - Designing Multi-Agent Collaboration4
- 2.1Concepts of Multi-Agent Systems (Coordination, Communication, Specialization)
- 2.2Architectural Patterns for Multi-Agent Collaboration (e.g., hierarchical, peer-topeer)
- 2.3Role-Based Agent Design
- 2.4Hands-on: Building a simple two-agent system that collaborates on a task (e.g., a “Researcher” agent and a “Summarizer” agent).
- DAY 3 - Advanced Agent Planning & Reflection4
- DAY 4 - Agent Evaluation & Debugging in Complex Systems4
- DAY 5 - Capstone Project & Future Trends3
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