What are the prerequisites for taking this course?

The prerequisites include Python programming knowledge, a basic understanding of Machine Learning, and Data Structures & Algorithms fundamentals.

What topics are covered in the course?

The course covers a wide range of topics, including the Transformer Architecture, Language Models & Embeddings, Advanced Learning Paradigms, Knowledge Integration & Retrieval, and Ethics & Contemporary Models.

How can I access the course materials?

You can access the course materials through the UBOS Asset Marketplace.

UBOS is a full-stack AI Agent Development Platform that helps businesses orchestrate AI Agents, connect them with enterprise data, and build custom AI Agents with LLMs and Multi-Agent Systems.

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. MCP servers act as bridges, allowing AI models to access and interact with external data sources and tools.

How can I contribute to the course?

You contribute by forking the repository, creating a feature branch, committing your changes, pushing to the branch, and creating a Pull Request.

Introduction to Large Language Models (LLMs) - NPTEL Course

Q: What is the NPTEL course on LLMs?

The NPTEL course on LLMs is a comprehensive course on Large Language Models offered by IIT Delhi and IIT Bombay through NPTEL (National Programme on Technology Enhanced Learning).

A comprehensive course on Large Language Models offered by IIT Delhi and IIT Bombay through NPTEL (National Programme on Technology Enhanced Learning).

Course Overview 📚

Instructors

Prof. Tanmoy Chakraborty (IIT Delhi)
Prof. Soumen Chakrabarti (IIT Bombay)

Teaching Assistants

Anwoy Chatterjee (PhD student, IIT Delhi)
Poulami Ghosh (PhD student, IIT Bombay)

Course Structure 🎓

Weekly Modules

Week 1: Foundations
- Introduction and Recent Advances
- Introduction to Natural Language Processing
- Deep Learning Basics
Week 2-8: Core Content
- Transformer Architecture
- Language Models & Embeddings
- Advanced Learning Paradigms
- Knowledge Integration & Retrieval
- Ethics & Contemporary Models

Getting Started 🚀

Prerequisites

Python programming knowledge
Basic understanding of Machine Learning
Data Structures & Algorithms fundamentals

Local Development

# Install dependencies
pnpm install

# Start development server
pnpm dev

# Visit http://localhost:3000

Website Features 💡

Technical Features

Built with Nextra documentation framework
React-based components
MDX support for interactive content
Dark/light mode theming
Full-text search capability
Mobile-responsive design

Content Features

Interactive code examples
Downloadable lecture materials
Progress tracking
Embedded diagrams and visualizations
Searchable documentation

Contributing 🤝

We welcome contributions to improve the course materials:

Fork the repository
Create your feature branch
Commit your changes
Push to the branch
Create a Pull Request

Resources 📖

Additional Reading

Speech and Language Processing
Neural Network Models for NLP
Course-specific materials in the /resources directory

Support

For technical issues, please open a GitHub issue. For course-related queries, use the NPTEL discussion forum.

License

This project is licensed under the MIT License. See LICENSE for details.

Built with Nextra | Deployed on Vercel

Introduction to Large Language Models (LLMs) - NPTEL Course