Advanced Agentic AI Techniques

अवलोकन

This course equips learners with the essential skills and knowledge to design and implement sophisticated agent-based systems. The course covers long-term memory integration within agents, emphasizing the LangGraph framework.

Participants explore multi-agent architectures and state management, focusing on effective orchestration and data routing. Through hands-on projects, learners will implement agentic systems, culminating in the development of an Autonomous Knowledge Agent.

पाठ्यक्रम

• Course Introduction
Meet your instructors and get an overview of advanced agentic systems and course structure.
• Long-Term Agent Memory
Explore long-term agent memory: understand semantic, episodic, and procedural memories. Learn storage strategies and best practices for personalized, coherent interactions.
• Long-Term Agent Memory in LangGraph
Learn how to persist agent memory in LangGraph using databases like SQLite and enhance long-term AI memory with vector storage via LangMem for robust, session-aware agents.
• Designing Multi-Agent Architecture
Explain the core components of multi-agent systems and how to design their high-level architecture.
• Designing Multi-Agent Architectures with LangGraph
Explore foundational multi-agent architecture patterns using LangGraph. Design, implement, and visualize orchestrated and peer-to-peer agent workflows for real-world scenarios.
• State Management in Multi-Agent Systems
Evaluate methods for tracking and updating agent state across multi-turn interactions.
• Implementing Multi-Agent Architectures with LangGraph
Learn to design, implement, and orchestrate multi-agent workflows using LangGraph for structured, auditable, and automated content pipelines with specialized agents and custom state.
• Orchestrating Agent Activities
Apply orchestration techniques to coordinate multiple agent actions and achieve complex workflows.
• Orchestrating Agent Activities with LangGraph
Learn to orchestrate multi-agent workflows with LangGraph, using supervisors, handoffs, tool-calling, and structured state management for scalable, modular agent systems.
• Routing and Data Flow in Agentic Systems
Configure routing mechanisms to manage data flow among agents in multi-agent systems.
• Implementing Data Routing in Agentic Systems with LangGraph
Learn to implement content-based, round-robin, and priority-based data routing in agentic systems using LangGraph, Pydantic, and LangChain frameworks.
• Building Agents Project: Autonomous Knowledge Agent
In this project, you will develop UDA-Hub, an intelligent, multi-agent decision suite capable of resolving customer support tickets across multiple platforms.

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द्वारा पढ़ाया गया

Henrique Santana, Christopher Agostino and Joshua Bernhard

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विषय

Computer Science