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LLM Application Fundamentals with LangChain

Intermediate3 hr

Learn to build conversational LLM applications — with reliable structured output, persistent conversation history, and real-time streaming.

Python2 hr - 4 hr3,500 XP1Statement of accomplishment

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Course Description

A description of the course.

Prerequisites

Curriculum

Course outline

1

Application Foundations

  • Your First AI App

    You will build a complete, functioning Gen AI application from scratch — from understanding the architecture and setting up LangChain, through creating prompt templates and model interfaces, to building a Gradio UI — giving you a hands-on feel for what AI engineering involves.

  • Application Development

    You will learn to build practical LLM applications from the ground up — from setting up authentication and importing LangChain, through validating user inputs and parsing structured outputs, to implementing comprehensive error handling — enabling you to create robust, production-ready applications that safely integrate LLMs into real-world workflows.

2

Conversational Applications

  • Conversation Fundamentals

    You will learn to build conversational AI applications that maintain context across multiple exchanges — from understanding message structures and designing chatbot prompts, through implementing conversation logic and UI with Gradio, to persisting conversations in databases — enabling you to create interactive, stateful chatbots that provide natural back-and-forth interactions.

  • Streaming Responses

    You will learn to implement streaming for real-time response delivery in conversational applications — from understanding token-based streaming and Python yield generators to building stream handlers in UI — enabling you to deliver responsive chatbots with immediate, incremental output.

LLM Application Fundamentals with LangChain

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