Intelligent Document Processing with OpenAI GPT & LangChain
Build a production-ready AI document extraction system using OpenAI, LangChain, FastAPI, Pydantic, MongoDB and Python
Updated on Jun, 2026
Language - English
Programming,Data Science,Artificial Intelligence
Lectures -121
Quizzes -1
Resources -30
Duration -18.5 hours
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Course Description
Unlock the power of Generative AI, Vision AI, and Backend Engineering by building a complete AI-powered document extraction system from scratch using Python, FastAPI, MongoDB, Pydantic, LangChain, and OpenAI.
This comprehensive hands-on course is designed for developers, AI engineers, backend developers, data professionals, and tech enthusiasts who want to learn how modern AI applications are built in real production environments. Instead of learning tools in isolation, you will build an end-to-end intelligent document processing pipeline that combines Large Language Models (LLMs), backend APIs, structured validation, and database integration into one scalable architecture.
Throughout this course, you will learn how to extract structured information from invoices, forms, PDFs, receipts, and business documents using advanced Vision LLMs and prompt engineering techniques.
What You Will Learn
By the end of this course, you will have the confidence to build and deploy intelligent AI applications capable of automating document processing workflows for finance, healthcare, logistics, retail, enterprise automation, and analytics systems.
Whether you are interested in Generative AI, AI Automation, Backend Development, LLM Engineering, or Document AI, this project-based course will help you gain practical industry-ready skills while building a strong portfolio project for your career.
Who This Course Is For
Basic Requirements
The following topics are helpful but not mandatory:
You do NOT need prior experience in:
This comprehensive hands-on course is designed for developers, AI engineers, backend developers, data professionals, and tech enthusiasts who want to learn how modern AI applications are built in real production environments. Instead of learning tools in isolation, you will build an end-to-end intelligent document processing pipeline that combines Large Language Models (LLMs), backend APIs, structured validation, and database integration into one scalable architecture.
Throughout this course, you will learn how to extract structured information from invoices, forms, PDFs, receipts, and business documents using advanced Vision LLMs and prompt engineering techniques.
What You Will Learn
- MongoDB & Database Engineering
- MongoDB Atlas setup
- CRUD operations
- Document schema design
- Persistent AI data storage
- Pydantic Data Validation
- Structured JSON validation
- AI response verification
- Data modeling
- Error prevention and schema enforcement
- FastAPI Backend Development
- REST API development
- Backend architecture
- Request & response modeling
- Database integration with APIs
- LangChain & OpenAI Integration
- Prompt engineering
- Vision AI workflows
- LLM response parsing
- Structured AI extraction pipelines
- Document Processing App with FastAPI and LLMs
- Invoice data extraction
- PDF understanding
- Form and receipt analysis
- Intelligent business document automation
- Deploy App in Render
- Scalable backend systems
- Reliable AI workflows
- Clean code practices
- Real-world AI architecture design
By the end of this course, you will have the confidence to build and deploy intelligent AI applications capable of automating document processing workflows for finance, healthcare, logistics, retail, enterprise automation, and analytics systems.
Whether you are interested in Generative AI, AI Automation, Backend Development, LLM Engineering, or Document AI, this project-based course will help you gain practical industry-ready skills while building a strong portfolio project for your career.
Who This Course Is For
- Python developers who want to enter AI Engineering
- Backend developers interested in Generative AI
- Students and beginners wanting to build real AI applications
- AI enthusiasts interested in Document AI and Vision Models
- Developers looking to build production-ready AI systems
- Anyone interested in FastAPI, MongoDB, LangChain, and OpenAI integration
Goals
- Build real-world AI-powered document extraction applications using Python, FastAPI, MongoDB, LangChain, and OpenAI
- Learn how to create production-ready Generative AI pipelines for invoices, forms, PDFs, and business documents
- Master structured data extraction using Vision LLMs and prompt engineering techniques
- Develop scalable backend APIs with FastAPI for AI and document processing systems
- Learn MongoDB integration for storing and managing AI extraction results
- Validate and enforce structured AI responses using Pydantic data models
- Build reliable AI workflows instead of simple prototype scripts
- Understand how to connect LLMs with databases, APIs, and real backend architectures
- Learn end-to-end AI application development from data ingestion to deployment
- Create modular, maintainable, and scalable Python applications
- Design intelligent document processing systems used in modern AI automation platforms
- Gain hands-on experience with AI engineering, backend development, and data validation
- Learn industry-level architecture for AI-powered business automation systems
- Build practical portfolio projects for AI Engineering, Generative AI, and Backend Development roles
- Understand how to deploy and scale AI applications for real-world production environments
Prerequisites
This course is designed in a beginner-friendly yet industry-focused way. You do not need advanced AI or backend experience to get started.Basic Requirements
- Basic understanding of Python programming
- Familiarity with writing simple Python scripts and functions
- Basic knowledge of installing Python packages using pip
- A computer with internet connection (Windows, Mac, or Linux)
The following topics are helpful but not mandatory:
- Basic understanding of APIs
- Basic database concepts
- Beginner-level understanding of JSON data
- Basic command line or terminal usage
You do NOT need prior experience in:
- Generative AI
- LangChain
- FastAPI
- MongoDB
- OpenAI APIs
- Pydantic
- Vision AI
- Backend development
- LLM engineering
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
8 Lectures
-
About Course - What you will learn
03:48
03:48
-
Introduction
06:09
06:09
-
Course Plan
13:32
13:32
-
Setting up Course
07:37
07:37
-
Download Folder Structure [Do Not Skip]
03:38
03:38
-
Install Poetry and Initialize Project
08:48
08:48
-
Add Packages in Poetry
07:36
07:36
-
Setting Up Environment
08:55
08:55
Download Resources
2 Lectures
Fundamentals of Python Programming [Optional]
13 Lectures
MongoDB Atlas and Pymongo
19 Lectures
Type Hinting
10 Lectures
Pydantic Data Model | Data Validation
8 Lectures
API and HTTP
9 Lectures
FastAPI
14 Lectures
LangChain
9 Lectures
Project | Intelligent Document Processing
12 Lectures
Project | Web App
12 Lectures
Deploy Web App on Cloud with Docker
5 Lectures
Instructor Details
VedicSkill Academy
Your learning compass
We are VedicSkill Academy, an innovative learning platform dedicated to empowering students through a practical, hands-on approach to education. Our expertise spans across Data Science, Machine Learning, Statistics, and Generative AI, enabling us to deliver courses that are both insightful and industry-relevant.
At VedicSkill Academy, we don’t just teach—we guide and mentor you throughout your learning journey, ensuring you gain real-world skills and confidence. Our team is always ready to support you by answering course-related queries and providing personalized guidance whenever needed.
At VedicSkill Academy, we don’t just teach—we guide and mentor you throughout your learning journey, ensuring you gain real-world skills and confidence. Our team is always ready to support you by answering course-related queries and providing personalized guidance whenever needed.
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