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CloudaQube

Ai Ml · intermediate

Building RAG Applications

A hands-on, intermediate course on Retrieval-Augmented Generation (RAG). Move beyond basic prompting and learn to build production-grade RAG pipelines using LangChain and LlamaIndex — covering text chunking, embedding models, vector stores, hybrid retrieval, advanced patterns like HyDE and query decomposition, and evaluation with RAGAS. Every module includes real Python code you can run today.

  • 8 hours
  • 20 lessons
  • 6 modules
  • updated May 2026
Module 1 freeNo credit cardFull course from $8.99/mo
try it

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 · 30 min

What is RAG and Why Does It Matter?

Large language models are powerful but fundamentally limited by two constraints: their knowledge cutoff (they cannot know what happened after training) and their context window (they cannot ingest an entire enterprise…
question 1 of 3 · from the Module 1 quiz
What is the primary motivation for using RAG instead of relying solely on an LLM''s parametric knowledge?
Pick an answer.
curriculum

6 modules, 20 lessons

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

  • readWhat is RAG and Why Does It Matter?30 min
  • quizQuiz: RAG Fundamentals15 min
  • videoVideo: RAG Fundamentals15 min
how it's built

Built by the CloudaQube team

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

  • 01 6 module quizzes — every answer comes with an explanation.
  • 02 Last updated May 2026.
  • 03 Any module can become a hands-on lab in Labs Studio.
outcomes

What you'll be able to do

  • 01 Explain the naive RAG pipeline and its limitations
  • 02 Implement fixed-size, semantic, and sentence-window chunking strategies
  • 03 Choose and configure embedding models for production use cases
  • 04 Deploy and query FAISS, pgvector, and Pinecone vector stores
  • 05 Build hybrid search pipelines combining dense and sparse retrieval
  • 06 Apply advanced patterns including HyDE, query decomposition, and parent-child chunking
  • 07 Evaluate RAG systems using RAGAS metrics and trace pipelines with LangSmith
before you start
  • — Intermediate Python (list comprehensions, classes, async)
  • — Basic understanding of LLMs and prompt engineering
  • — Familiarity with pip and virtual environments
questions

Before you start

How long does it take?

About 8 hours of lessons, videos and hands-on walkthroughs across 6 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 6 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 RAG Applications — Online Course | CloudaQube