Overview

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Master the design and deployment of advanced agentic AI systems using LangGraph and LangChain. Learn to build multi-agent architectures, implement robust production strategies, and ensure secure, scalable AI deployments. This course takes you deep into the world of LangGraph, covering its unique graph-based architectures and advanced agent patterns. You will learn to construct multi-agent systems, implement communication and coordination strategies, and design hierarchical and iterative agent workflows. The course also covers critical production deployment topics, including observability, security, testing, cost optimization, and real-world deployment practices, empowering you to launch and maintain production-ready AI agent systems. With a focus on advanced concepts and real-world deployment, this course uses detailed explanations, practical demonstrations, and targeted quizzes to help you design, secure, and deploy sophisticated agentic AI applications. Each module builds your expertise in both architecture and operational best practices. This course is part three of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Agentic AI Systems: Build & Deploy with LangChain/LangGraph, by Paulo Dichone. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Syllabus

LangGraph - A Full Deep Dive
- This module provides a comprehensive exploration of LangGraph, focusing on building and managing stateful agentic workflows. Learners will gain hands-on experience with graph creation, dynamic routing, and human-in-the-loop integration. The content emphasizes practical implementation of complex AI systems using graph-based architectures.
Multi-Agent Systems with LangGraph and LangChain
- This module explores the design and implementation of multi-agent systems using LangChain and LangGraph, covering key concepts like agent communication, coordination, and task distribution. Learners will gain hands-on experience with patterns such as ReAct, Map-Reduce, and message passing to build scalable and collaborative agent systems. The module also emphasizes best practices for error handling, state management, and hierarchical system design.
Production Deployment - Deploying AI Agents
- This module covers essential practices for deploying AI agents in production, including observability, security measures, testing strategies, and system resilience. Learners will gain hands-on experience with tools like LangSmith, LLM Guard, and FastAPI, while learning to implement robust error handling, caching, and monitoring solutions.
Wrap up
- This module provides a comprehensive review of the key concepts covered in the course and offers practical guidance on how to continue developing and deploying agentic AI systems. Learners will gain insights into next steps for further learning and application.

Taught by

Packt - Course Instructors

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