📘
Winter LLM Bootcamp
  • Welcome to the course. Bienvenue!
    • Course Structure
    • Course Syllabus and Timelines
    • Know your Educators
    • Action Items and Prerequisites
    • Bootcamp Kick-Off Session
  • Basics of LLMs
    • What is Generative AI?
    • What is a Large Language Model?
    • Advantages and Applications of LLMs
    • Bonus Resource: Multimodal LLMs and Google Gemini
  • Word Vectors, Simplified!
    • What is a Word Vector
    • Word Vector Relationships
    • Role of Context in LLMs
    • Transforming Vectors into LLM Responses
    • Bonus Section: Overview of the Transformers Architecture
      • Attention Mechanism
      • Multi-Head Attention and Transformers Architecture
      • Vision Transformers
    • Graded Quiz 1
  • Prompt Engineering and Token Limits
    • What is Prompt Engineering
    • Prompt Engineering and In-context Learning
    • Best Practices to Follow
    • Token Limits and Hallucinations
    • Prompt Engineering Excercise (Ungraded)
      • Story for the Excercise: The eSports Enigma
      • Your Task for the Module
  • Retrieval Augmented Generation (RAG) and LLM Architecture
    • What is Retrieval Augmented Generation (RAG)
    • Primer to RAG: Pre-trained and Fine-Tuned LLMs
    • In-Context Learning
    • High-level LLM Architecture Components for In-Context Learning
    • Diving Deeper: LLM Architecture Components
    • Basic RAG/LLM Architecture Diagram with Key Steps
    • RAG versus Fine-Tuning and Prompt Engineering
    • Versatility and Efficiency in RAG
    • Understanding Key Benefits of Using RAG in Enterprises
    • Hands-on Demo: Performing Similarity Search in Vectors (Bonus Module)
    • Using kNN and LSH to Enhance Similarity Search (Bonus Module)
    • Graded Quiz 2
  • Hands-on Development
    • Prerequisites
    • Dropbox Retrieval App
      • Understanding Docker
      • Building the Dockerized App
      • Retrofitting our Dropbox app
    • Amazon Discounts App
      • How the project works
      • Repository Walkthrough
    • How to Run 'Examples'
    • Bonus Section: Real-time RAG with LlamaIndex and Pathway
  • Bonus Resource: Recorded Interactions from the Archives
  • Final Project + Giveaways
    • Prizes and Giveaways
    • Suggested Tracks for Ideation
    • Form for Submission
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Welcome to the course. Bienvenue!

NextCourse Structure

Last updated 1 year ago

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Embark on your thrilling adventure into the realm of Large Language Models (LLMs)!

This bootcamp, offered at no cost as a cohort-based course, is designed to be your all-encompassing tutorial for mastering and creating RAG (Retrieval-Augmented Generation) applications, leveraging the capabilities of Large Language Models (LLMs) and live/real-time data streams.

If this concept seems daunting, that's perfectly okay. By the time you complete this bootcamp, not only will you have a deep appreciation for these advanced techniques and technologies, but you'll also be equipped to develop a significant open-source project independently!

This course is offered as a collaborative initiative by the Programming Club at IIT Kanpur, the Club of Programmers at IIT (BHU) Varanasi, the SnT Council at IIT (BHU) Varanasi, and Pathway.

In the Next Module: You will delve into the structure of the course, get acquainted with its creators, understand what you can gain from participating, and understand your role as a learner.

Please make sure to finish your and star the GitHub repositories mentioned below. We will be referring back to these resources throughout the course.

⭐
registration here
https://github.com/pathwaycom/pathway
https://github.com/pathwaycom/llm-app