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RAG and LLM Bootcamp
  • Welcome to the Bootcamp
    • Course Structure
    • Course Syllabus and Timelines
    • Know your Educators
    • Action Items and Prerequisites
    • Kick-Off Session for the Bootcamp
  • 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: Overview of the Transformer Architecture
      • Attention Mechanism
      • Multi-Head Attention and Transformer Architecture
      • Vision Transformers (ViTs)
    • Bonus: Future of LLMs? | By Transformer Co-inventor
    • Graded Quiz 1
  • Prompt Engineering and Token Limits
    • What is Prompt Engineering
    • Prompt Engineering and In-context Learning
    • For Starters: Best Practices
    • Navigating Token Limits
    • Hallucinations in LLMs
    • Prompt Engineering Excercise (Ungraded)
      • Story for the Excercise: The eSports Enigma
      • Your Task fror 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 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)
    • Bonus Video: Implementing End-to-End RAG | 1-Hour Session
    • Graded Quiz 2
  • Hands-on Development
    • Prerequisites (Must)
    • Docker Basics
    • Your Hands-on RAG Journey
    • 1 – First RAG Pipeline
      • Building with Open AI
      • How it Works
      • Using Open AI Alternatives
      • RAG with Open Source and Running "Examples"
    • 2 – Amazon Discounts App
      • How the Project Works
      • Building the App
    • 3 – Private RAG with Mistral, Ollama and Pathway
      • Building a Private RAG project
      • (Bonus) Adaptive RAG Overview
    • 4 – Realtime RAG with LlamaIndex/Langchain and Pathway
      • Understand the Basics
      • Implementation with LlamaIndex and Langchain
  • Final Project + Giveaways
    • Prizes and Giveaways
    • Suggested Tracks for Ideation
    • Sample Projects and Additional Resources
    • Submit Project for Review
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  • In the Next Module

Welcome to the Bootcamp

NextCourse Structure

Last updated 9 months ago

We are about to embark on a short but exciting journey 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, you will have a deep appreciation for these advanced techniques and technologies, and be equipped to develop a significant open-source project independently!

  • https://github.com/pathwaycom/pathway

  • https://github.com/pathwaycom/llm-app

Course Offered By

This course is offered as a collaborative initiative by Developers' Society BITS Goa and Pathway.

  • About Pathway (https://pathway.com): Pathway is a Python ETL framework for event processing, real-time analytics, LLM pipelines, and RAG. It is the world's fastest data processing engine, supporting unified workflows for batch, streaming, and LLM applications. Developed in Rust and accessible through Python, it requires only Python proficiency to leverage its capabilities.

  • About Developers' Society, BITS Goa: DevSoc BITS Pilani Goa is the student guild at BITS Pilani, K K Birla Goa Campus, dedicated to fostering the growth and development of students interested in Software Engineering, Data Science, and related fields.

In the Next Module

You will explore 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 registration via this Google Form and star the GitHub repositories mentioned below. It's your way to support our work and join the Pathway community. We will also refer back to these resources within the course.

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