📦 Module 0: Introduction & Environment Setup

[malibayram]

📦 Module 0: Introduction & Environment Setup

This module covers the foundational concepts and environment setup for building LLMs from scratch.

Tasks to Complete:

• Lesson 0.1 — Welcome to the LLM Revolution

  • Create course introduction video (~25 mins)
  • Explain course goals and what we will build
  • Cover why learn LLMs from scratch
  • Compare open-source vs closed-source models (GPT-4 vs LLaMA 3)

• Lesson 0.2 — Core Concepts: Autoregression, Transformers, Pretraining vs Fine-tuning

  • Explain autoregressive language modeling
  • Introduce Transformer architecture concepts
  • Distinguish between pretraining and fine-tuning

• Lesson 0.3 — Setting Up Your Deep Learning Environment

  • Python environment setup guide
  • Install PyTorch
  • Install required packages: datasets, tiktoken, transformers
  • GPU setup instructions for Colab/Kaggle
  • Create environment setup notebook

Deliverables:

• 3 video lectures (~25 minutes each)
• Environment setup Colab notebook
• Installation guide documentation
• Quiz for module completion

Resources:

• Course description and learning outcomes
• Prerequisites verification checklist