Packt

Intelligent Retrieval and Agent Architectures with LangChain

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Packt

Intelligent Retrieval and Agent Architectures with LangChain

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Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Build intelligent RAG systems and implement advanced vector indexing for scalable solutions.

  • Design and deploy intelligent agents and multi-agent systems using LangChain.

  • Implement error handling, consensus mechanisms, and advanced reasoning for reliable AI applications.

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Recently updated!

June 2026

Assessments

3 assignments

Taught in English

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This course is part of the Generative AI with LangChain Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

This module explores how Retrieval-Augmented Generation (RAG) systems enhance language models by integrating external knowledge sources. Learners will examine the architecture and components of RAG pipelines, including vector indexing, document chunking, and advanced retrieval techniques. Practical applications, such as building a corporate documentation chatbot, are also covered.

What's included

1 video8 readings1 assignment

This module explores how to build intelligent agentic applications using large language models (LLMs) and LangChain. Learners will discover how to integrate, define, and customize tools, handle errors, and leverage advanced tool-calling strategies to enable agents to interact with the world and solve complex tasks. Practical examples and best practices for planning, workflow management, and robust agent design are included.

What's included

1 video9 readings1 assignment

This module explores advanced techniques for designing and orchestrating intelligent agents, including multi-agent collaboration, consensus mechanisms, and reasoning path decomposition. Learners will gain hands-on experience with frameworks like LangGraph and LangChain, and discover how algorithms such as Monte Carlo Tree Search can optimize agent decision-making. By the end, you'll understand how to build, manage, and deploy sophisticated agentic applications.

What's included

1 video7 readings1 assignment

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