Advanced Agentic AI Techniques

Overview

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.

Syllabus

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.