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LLM App Development: Building Powered Applications with LangChain

Master the fundamentals of LangChain to build LLM-powered applications. This beginner-friendly course guides you through prompt templates, chains, agents, conversational memory, and document loaders using Python and OpenAI.

Khan Academy
Khan Academy@khanacademy
Published Jul 6, 2026
Updated Jul 6, 2026
LLM App Development: Building Powered Applications with LangChain
16m
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Course Overview

Welcome to LLM App Development: Building Powered Applications with LangChain. This hands-on course is designed to take you from a beginner to confidently building LLM-powered applications using the LangChain framework.

What You'll Learn

  • LLMs vs ChatModels: Understand the core distinctions between standard text-completion models and structured, message-based chat models.
  • Prompt Templates: Design reusable and dynamic blueprints to efficiently format inputs for language models.
  • Chains: Construct execution pipelines linking prompts, LLMs, and other utility chains.
  • Agents and Tools: Build systems where the LLM dynamically decides which actions to take and external tools to execute.
  • Memory: Implement conversational memory to persist state across multiple interactions.
  • Document Loaders: Load external data source files to perform custom question-answering.

Prerequisites

  • Basic proficiency in Python programming.
  • An active OpenAI API key for running model interactions.
  • A development environment (like VS Code) set up on your machine.

Tools & Technologies

  • Python
  • LangChain
  • OpenAI API
  • VS Code

Course Content

2Chapters4Lessons2Quizzes
1

Introduction to LangChain and Model Interfaces

2 lessons · 8mQuiz
1

Understanding LLMs and ChatModel Interfaces

4:10
2

Creating Dynamic Inputs with Prompt Templates

4:08
2

Building Workflows: Chains, Agents, and Memory

2 lessons · 8mQuiz
1

The Probabilistic Foundations of LLMs and LangChain Chains

4:09
2

Empowering Models with Agents, Tools, and Conversational Memory

4:09

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