🌿
Spring of Realtime LLMs
  • Get started with the Bootcamp!
    • Course Structure
    • Course Syllabus and Timelines
    • Know your Educators
    • Action Items and Prerequisites
    • Bootcamp Introductory Session | National Science Day
  • 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 (Early Access)
    • 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
  • 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 Architecture with the Key Components
    • RAG versus Fine-Tuning and Prompt Engineering
    • Versatility and Efficiency in RAG
    • Key Benefits of using RAG in an Enterprise/Production Setup
    • 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
    • 1 – Dropbox Retrieval App
      • Understanding Docker
      • Build the Dockerized App
      • Retrofitting our Dropbox app
    • 2 – Amazon Discounts App
      • How the Project Works
      • Building the App
    • 3 – RAG with Open Source and Running "Examples"
    • 4 (Bonus Section) – Realtime RAG with LlamaIndex and Pathway
      • Understanding the Basics
      • Implementation
      • Sample Business Use-case
  • Bonus Resource: Recorded Interactions from the Archives
  • Final Project + Giveaways
    • Prizes and Giveaways
    • Suggested Tracks for Ideation
    • Form for Submission
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  1. Get started with the Bootcamp!

Bootcamp Introductory Session | National Science Day

PreviousAction Items and PrerequisitesNextBasics of LLMs

Last updated 1 year ago

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If you could not join us live for the introductory session on 2nd March, this sub-module ensures you're caught up and ready to embark on this learning journey. This is a 1.5 hour session recording featuring Mudit Srivastava from Pathway and Nisarg Bhavsar from IIT Kharagpur. This conversation lays the foundation for your expectations throughout the course, highlighting key areas and insights.

In this session, you will gain:

  • Basic Knowledge of LLMs and RAG: An introduction to Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), discussing their significance and impact on the industry.

  • Course Structure and Cohort Insights: An overview of the course structure and a glimpse into our diverse and vibrant cohort.

  • Bootcamp Rewards: Information on the rewards for completing the Bootcamp, acknowledging your dedication and achievements.

Quick Introduction to the Bootcamp Enablers

This Bootcamp is supported by a collaboration between several organizations:

As you navigate through this module and the course, we aim to provide a learning experience that is both informative and inspiring!

Pathway (): Pioneering in data processing technology, Pathway presents the world's most efficient engine for managing batch, streaming, and LLMOn applications. Its development in Rust and accessibility through Python make it a crucial tool for those interested in data processing and analysis.

Kharagpur Data Analytics Group, KDAG (): Based out of IIT Kharagpur, KDAG is a student driven research group aimed at bringing Data Analytics and Machine Learning enthusiasts together under the umbrella of a single society. If unattended, IIT Kharagpur or "IIT KGP", a premier public research institute, and is the institute is the first of the IITs.

https://pathway.com
https://www.kdagiitkgp.org