The Complete LangChain & RAG Developer Course 2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English (US) | Duration: 3 h | Size: 2.31 GB
Build Production-Ready AI Applications with LangChain, OpenAI, FAISS & ChromaDB
Master Retrieval-Augmented Generation (RAG) and Build Real AI Systems from Scratch
Are you ready to master one of the
most in-demand skills in Generative AI engineering
?
Welcome to
The Complete LangChain & RAG Developer Course 2026
- a hands-on, beginner-friendly course designed to help you build powerful AI applications using
LangChain, OpenAI, FAISS, ChromaDB,
and
Retrieval-Augmented Generation (RAG)
.
In this course, you'll learn how modern AI systems like ChatGPT-style assistants retrieve real-time knowledge from PDFs, documents, databases, and custom data sources to generate
accurate, context-aware responses
.
This is not just theory.
You will build a
complete end-to-end RAG application
using real-world workflows and industry-standard tools used by modern AI engineers.
What You'll Learn
By the end of this course, you will be able to:
Understand how
Retrieval-Augmented Generation (RAG)
works
Build AI applications powered by
LangChain
Process
PDFs, CSVs, and DOCX
files
for AI pipelines
Master
text
chunking strategies
for better retrieval accuracy
Generate embeddings and perform
semantic similarity search
Work with vector databases like
FAISS
and
ChromaDB
Build scalable
LangChain
runnable pipelines
Create
production-ready AI retrieval systems
Use
prompt engineering
for better LLM responses
Structure outputs
using
Pydantic
Build a complete
Capstone RAG Project
from scratch
Why Learn RAG & LangChain?
Traditional Large Language Models (LLMs) are powerful - but they suffer from:
Hallucinations
Outdated knowledge
No access to private data
Limited context windows
Retrieval-Augmented Generation (RAG)
solves these problems by combining:
Large Language Models (LLMs)
Semantic Search
Embeddings
Vector Databases
Intelligent Retrieval Pipelines
This technology powers:
AI Assistants
Enterprise Chatbots
Knowledge Bases
Document Q&A Systems
AI Search Engines
Customer Support AI
Internal Company GPTs
RAG Engineers
and
LangChain Developers
are becoming some of the most sought-after professionals in AI today.
What Makes This Course Different?
Unlike many tutorials that only cover isolated concepts, this course focuses on:
Practical implementation
Real-world workflows
Beginner-friendly explanations
Step-by-step coding
Industry-standard architecture
Production-oriented development
You won't just learn concepts.
You'll build
real AI systems
.
Course Curriculum Overview
Module 1 - RAG Foundations & LangChain Kickstart
Learn the fundamentals of
Retrieval-Augmented Generation
and build your first AI-powered application using
LangChain
and
OpenAI
.
Module 2 - Document Loading & Multi-Format Data Ingestion
Teach your AI to process
PDFs, CSV files,
and
DOCX documents
using practical LangChain loaders.
Module 3 - Smart Text Chunking & Retrieval Optimization
Master chunking strategies that dramatically improve retrieval quality and response accuracy.
Module 4 - Embeddings, Semantic Search & Vector Databases
Understand embeddings, vector search,
FAISS, ChromaDB,
and semantic similarity in depth.
Module 5 - LangChain Runnables & AI Pipeline Composition
Build modular, scalable AI workflows using
LangChain runnables
and chaining techniques.
Module 6 - Capstone Project: Build a Complete End-to-End RAG Application
Bring everything together by building a
production-ready RAG pipeline
from scratch.
You will:
Load documents
Chunk text intelligently
Generate embeddings
Build a retriever
Create runnable chains
Engineer prompts
Parse structured outputs
Test and validate the final AI system
Tools & Technologies Covered
LangChain
OpenAI API
Python
FAISS
ChromaDB
Embeddings
Vector Databases
Semantic Search
Pydantic
Runnable Chains
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Who This Course Is For
This course is perfect for:
Python Developers
AI Engineers
Machine Learning Enthusiasts
LangChain Beginners
Generative AI Developers
Software Engineers
Students entering the AI industry
Anyone wanting to build AI-powered applications
Prerequisites
Basic Python knowledge is recommended.
No prior experience with the following is required:
LangChain
Vector Databases
RAG
Embeddings
Semantic Search
Everything is taught
step-by-step
in a beginner-friendly manner.
Start Building Real AI Applications Today
If you want to become a modern AI developer and master one of the
most important technologies in Generative AI
, this course is for you.
Join now and start building
production-ready RAG applications
with
LangChain, OpenAI, FAISS,
and
ChromaDB
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