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CloudaQube

Ai Ml · generic · intermediate

Building with LangChain & RAG

Build production-ready LLM applications using LangChain. From core chains and memory management through document loading, vector stores, retrieval-augmented generation, and autonomous agents. Based on DeepLearning.AI's LangChain series: LangChain for LLM Application Development, Chat with Your Data, and Building Systems with the ChatGPT API.

  • 9 hours
  • 35 lessons
  • 7 modules
  • updated April 2026
Module 1 freeNo credit cardFull course from $8.99/mo
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Try it before you sign up

Read a full lesson and answer 3 questions from the Module 1 quiz. No account needed.

free lesson · read · 15 min

LangChain Architecture Overview

LangChain is a framework for building LLM-powered applications. It provides abstractions for the most common patterns: prompting, chaining, memory, retrieval, and agents. LangChain is a framework with multiple…
question 1 of 3 · from the Module 1 quiz
What does the pipe operator (|) do in LangChain Expression Language (LCEL)?
Pick an answer.
curriculum

7 modules, 35 lessons

Module 1 is free — lessons, hands-on walkthrough and quiz.

  • readLangChain Architecture Overview15 min
  • videoLangChain Explained in 13 Minutes13 min
  • readOutput Parsers & Structured Data Extraction12 min
  • hands-onLab: LangChain Hello World25 min
  • quizQuiz: LangChain Foundations10 min
how it's built

Built by the CloudaQube team

No celebrity instructor — here is exactly what goes into the course instead.

  • 01 7 guided hands-on walkthroughs you run in a real environment.
  • 02 7 module quizzes — every answer comes with an explanation.
  • 03 Last updated April 2026.
  • 04 Any module can become a hands-on lab in Labs Studio.
outcomes

What you'll be able to do

  • 01 Build LLM applications using LangChain chains, prompts, and output parsers
  • 02 Implement conversation memory for multi-turn AI applications
  • 03 Load, split, and embed documents into vector stores for RAG
  • 04 Build a production-ready document Q&A chatbot with source attribution
  • 05 Evaluate RAG pipeline quality using RAGAS metrics
  • 06 Create LangChain agents with custom tools using the ReAct pattern
before you start
  • — Python programming (intermediate level)
  • — Basic understanding of LLMs and prompt engineering
questions

Before you start

How long does it take?

About 9 hours of lessons, videos and hands-on walkthroughs across 7 modules.

What’s free?

Module 1 in full — lessons, hands-on walkthrough and quiz — with no card required. Any paid plan (from $8.99/mo) unlocks all 7 modules, and starts with a 14-day free trial.

get started

Start the course with Module 1 free.

No card required. Unlock every module from $8.99/mo when you’re ready.

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      Building with LangChain & RAG — Online Course | CloudaQube