🚀
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
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  1. Introduction

Greetings from your Instructors

PreviousPrerequisitesNextFirst Exercise (Ungraded)

Last updated 1 year ago

Hello learners! Before we plunge into the captivating realm of Large Language Models, enjoy a special video greeting from one of your instructors, Adrian Kosowski (). Beyond his role as Chief Product Officer at Pathway and a father of two, Adrian is a seasoned researcher and entrepreneur. He earned his PhD in Computer Science at just 20 years old and has over 15 years of research experience. Adrian has co-authored 100+ research publications and co-founded Spoj.com, through which he impacted the lives of millions of programmers around the globe.

In this introductory video, you’ll get to meet Adrian and know:

  • Why Pathway is supporting this initiative and a brief introduction of Pathway

  • What you'll learn throughout this course

  • Immense importance of understanding LLMs in today's world

  • What you can expect to gain at the end of this course

Other Instructors and Course Contributors

A heartfelt thanks to those who made this course richer with their expertise:

  • Adrian Kosowski, CPO at Pathway | PhD at 20 | Prev - Professor at École Polytechnique and Co-founder of SPOJ | 100+ research publications

  • Anup Surendran, Head of Product Marketing & Growth at Pathway | Prev - VP at QuestionPro | Advisor, Texas A&M University

  • Jan Chorowski, CTO at Pathway | PhD in Neural Networks | Worked with Godfathers of AI | Former Researcher at Google Brain, MILA AI | 10K+ citations

  • Sergey Kulik, Lead Software Research Engineer and Solutions Architect at Pathway | IOI Gold Medalist | Prev - Head of Service at Yandex

  • Mudit Srivastava, Growth Manager at Pathway | Prev - Growth Head at AI Planet

  • Bobur Umurzokov, Developer Advocate at Pathway | Ex-Lead at Microsoft Tallinn

  • Berke Can Rizai, LLM Research Engineer at Pathway | Ex-Data Scientist at Getir

  • Olivier Ruas, R&D Engineer - Algorithms and Data Processing Magician at Pathway | Did PhD Focused on KNNs | Postdoc at Peking University

We especially thank Mike Chambers, Developer Advocate at Amazon Web Services for allowing us to cite some of his finest educational resources from the BuildOnAWS YouTube channel. Along with that we've also cited some wonderful open-resources published by IBM Technology, Microsoft, and others. We are highly thankful to them too.

Let's embark on this captivating voyage into the world of Large Language Models. Ready to dive in? 🌟

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