🚀
10 Days Realtime LLM Bootcamp
  • Introduction
    • Getting Started
    • Course Syllabus
    • Course Structure
    • Prerequisites
    • Greetings from your Instructors
    • First Exercise (Ungraded)
  • Basics of LLM
    • What is Generative AI?
    • What is a Large Language Model?
    • Advantages and Applications of Large Language Models
    • Bonus Resource: Multimodal LLMs
  • Word Vectors Simplified
    • What is a Word Vector
    • Word Vector Relationships
    • Role of Context in LLMs
    • Transforming Vectors into LLM Responses
      • Neural Networks and Transformers (Bonus Module)
      • Attention and Transformers (Bonus Module)
      • Multi-Head Attention and Further Reads (Bonus Module)
    • Let's Track Our Progress
  • Prompt Engineering
    • What is Prompt Engineering
    • Prompt Engineering and In-context Learning
    • Best Practices to Follow in Prompt Engineering
    • Token Limits in Prompts
    • Prompt Engineering Excercise
      • Story for the Excercise: The eSports Enigma
      • Tasks in the Excercise
  • Retrieval Augmented Generation and LLM Architecture
    • What is Retrieval Augmented Generation (RAG)?
    • Primer to RAG Functioning and LLM Architecture: Pre-trained and Fine-tuned LLMs
    • In-Context Learning
    • High level LLM Architecture Components for In-context Learning
    • Diving Deeper: LLM Architecture Components
    • LLM Architecture Diagram and Various Steps
    • RAG versus Fine-Tuning and Prompt Engineering
    • Versatility and Efficiency in Retrieval-Augmented Generation (RAG)
    • Key Benefits of RAG for Enterprise-Grade LLM Applications
    • Similarity Search in Vectors (Bonus Module)
    • Using kNN and LSH to Enhance Similarity Search in Vector Embeddings (Bonus Module)
    • Track your Progress
  • Hands-on Development
    • Prerequisites
    • Dropbox Retrieval App in 15 Minutes
      • Building the app without Dockerization
      • Understanding Docker
      • Using Docker to Build the App
    • Amazon Discounts App
      • How the Project Works
      • Step-by-Step Process
    • How to Run the Examples
  • Live Interactions with Jan Chorowski and Adrian Kosowski | Bonus Resource
  • Final Project + Giveaways
    • Prizes and Giveaways
    • Tracks for Submission
    • Final Submission
Powered by GitBook
On this page
  • About the bootcamp
  • Making the coursework available

Introduction

NextGetting Started

Last updated 1 year ago

Welcome to this exciting journey into the world of Large Language Models (LLMs)!

Please Note:

  • The same coursework is also available at the Institute Technical Council (ITC) IIT Bombay Website: . The link is open to everyone.

  • However, if you are not on the IIT Bombay campus and encounter any difficulties accessing the provided link, you can alternatively continue your learning here, on this link itself.

About the bootcamp

In November 2023, the Web & Coding Club at IIT Bombay and the AI Community at IIT Bombay, supported by the Institute Technical Council, joined hands with Pathway to launch this free, cohort-based course. This initiative, focusing on Generative AI, LLMs, and Real-time Data Processing, addressed the growing need to understand, leverage, and build Generative AI solutions.

Key highlights:

  • The course was shaped by contributions from global leaders in academia and deep learning, boasting past affiliations with prominent organizations like Google Brain, Mila-Quebec AI Institute, and Microsoft Research.

  • The bootcamp attracted over 1400 learners, including over 1000 students from IIT Bombay. Participants included students and professionals from HEC Paris, IIT Delhi, Indiana University, Qualcomm, and Novartis.

  • Despite the tight 10-day schedule, the bootcamp inspired active involvement. Various student developers went ahead to create interesting enterprise-centric apps. For example:

    • A project management assistant integrated with Slack, capable of delivering real-time insights from Trello Dashboards.

    • An LLM-powered application providing current insights into digital marketing trends influenced by ad spending data.

Making the coursework available

We're opening up our archived coursework for free, driven by our belief in the power of open education and Generative AI. This is an invitation for students and professionals to use these resources as a springboard for creating solutions that make a real difference.

This resource is particularly beneficial for those starting or looking to deeper into the world of Large Language Models (LLMs), Generative AI, Retrieval Augmented Generation (RAG), and related areas, providing a thorough educational guide.

Happy learning!

😄
https://itc.gymkhana.iitb.ac.in/AIC/realtime-llm-bootcamp/