6-Month Learning Path to LLM Development - Resource Guide

Phase 1: Programming Foundations (Weeks 1-4)

Core Learning Resources

• Python Fundamentals

  • Python for Everybody Specialization
  • Real Python Tutorials
  • Python Practice Problems

• Data Science Tools

  • Jupyter Notebook Tutorial
  • NumPy User Guide
  • Pandas User Guide
  • Matplotlib Tutorials

Projects

1. Data Analysis Dashboard

   • Dataset: Our World in Data COVID
   • Tutorial: Streamlit Dashboard Guide
   • Learning Resource: Plotly Graphing Library

2. Automated Data Pipeline

   • API: Alpha Vantage Documentation
   • Tutorial: Automation with Python
   • Resource: Python Schedule Library

Phase 2: Mathematics & ML Foundations (Weeks 5-8)

Core Learning Resources

• Mathematics

  • 3Blue1Brown Linear Algebra
  • Khan Academy Calculus
  • Khan Academy Statistics

• Machine Learning

  • Google's Machine Learning Crash Course
  • Scikit-learn Tutorials
  • Machine Learning with Python

Projects

1. Regression Analysis

   • Dataset: California Housing
   • Tutorial: Scikit-learn Regression Guide
   • Visualization: Seaborn Tutorial

2. Classification System

   • Dataset: Credit Card Fraud
   • Guide: Scikit-learn Classification
   • Metrics: Model Evaluation Guide

Phase 3: Deep Learning Foundations (Weeks 9-12)

Core Learning Resources

• Deep Learning Basics

  • Fast.ai Practical Deep Learning
  • Deep Learning Specialization
  • NYU Deep Learning Course

• PyTorch

  • PyTorch Tutorials
  • PyTorch Documentation
  • PyTorch Examples

Projects

1. Neural Network Implementation

   • Dataset: MNIST Database
   • Tutorial: PyTorch Neural Nets
   • Guide: Neural Network Implementation

2. Computer Vision Model

   • Dataset: CIFAR-10
   • Tutorial: PyTorch Vision Tutorial
   • Resource: Torchvision Documentation

Phase 4: NLP & Transformers (Weeks 13-16)

Core Learning Resources

• Stanford CS224N

  • Course Website
  • Lecture Videos
  • Key lectures:
    • Introduction and Word Vectors
    • Neural Nets and Backpropagation
    • Transformers
    • Natural Language Generation

• Hugging Face Resources

  • Course Home
  • Chapters:
    • Chapter 1: Transformer Models
    • Chapter 2: Using Transformers
    • Chapter 3: Fine-tuning
    • Chapter 4: Sharing Models
  • Model Hub
  • Datasets
  • Documentation

• Transformer Resources

  • The Illustrated Transformer
  • Illustrated Self-Attention
  • Attention Paper
  • Annotated Transformer

Projects

1. Text Classification System

   • Dataset: IMDB Reviews
   • Guide: Text Classification Tutorial
   • Deployment: FastAPI Documentation

2. Question-Answering System

   • Dataset: SQuAD
   • Tutorial: Question Answering Guide
   • Evaluation: QA Metrics

Phase 5: Advanced Training (Weeks 17-20)

Learning Resources

• Weights & Biases Tutorials
• PyTorch Lightning Tutorials
• Distributed Training Guide
• MLOps Guide

Projects

1. Custom Model Training

   • Distributed Training Tutorial
   • Model Parallel Best Practices
   • Mixed Precision Training

2. Production Deployment

   • Model Serving with TorchServe
   • MLflow Guide
   • Docker Documentation

Phase 6: LLM Development (Weeks 21-24)

Resources

• EleutherAI Resources
• Anthropic Research Papers
• OpenAI API Documentation
• LangChain Documentation

Projects

1. LLM Training

   • Hugging Face Training Guide
   • DeepSpeed Documentation
   • PEFT Library

2. LLM Application

   • LangChain Templates
   • Vector Database Guide
   • RAG Tutorial

Online Communities

• Hugging Face Forums
• PyTorch Forums
• ML Subreddit
• AI Stack Exchange