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Introduction to NLP and LLMs 2024

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Lecture Notes

  • Week 1: Introduction
    • Week 1 Session 1: Foundations and Evolution of NLP
    • Week 1 Session 2: The Revolution in Modern NLP
    • Week 1 Lab - Introduction to NLP Basics
  • Week 2: Basics of Text Preprocessing
    • Week 2 Session 1: Text Preprocessing Fundamentals
    • Week 2 Session 2: Advanced Text Preprocessing and Representation
    • Week 2 Session 3: Korean Text Preprocessing and Tokenization
  • Week 3: Fundamentals of Language Models
    • Week 3 Session 1: Introduction to Language Models and N-grams
    • Week 3 Session 2: Advanced Statistical Language Models
  • Week 4: Word Embeddings
    • Week 4 Session 1: Introduction to Word Embeddings and Word2Vec
    • Week 4 Session 2: Advanced Word Embeddings
  • Week 5: Transformers
    • Week 5 Session 1: Introduction to Transformers
    • Week 5 Session 2: BERT
    • Week 5 Session 3: Practical Implementation and Visualization of Transformers
  • Week 6: Understanding LLM APIs
    • Week 6 Session 1: Large Language Model (LLM) Basics and Training Strategies
    • Week 6 Session 2: Introduction to LLM APIs and OpenAI API Usage
    • Week 6 Session 3: Sampling Methods and Text Generation
  • Special Lecture: 2024 Nobel Prize in Physics
    • Session 1: Foundational Discoveries in Machine Learning with Artificial Neural Networks
    • Session 2: Deep Learning Evolution and Advanced Neural Network Architectures
    • Session 3: Insights from Interviews
  • Special Lecture: 2024 Nobel Prize in Chemistry
    • Session 1: Computational Protein Design and De Novo Protein Engineering
    • Session 2: Protein Structure Prediction Using Artificial Intelligence
    • Session 3: Insights from Interviews
  • Week 9: Basics of Prompt Engineering
    • Week 9 Session 1: Introduction to Prompt Engineering and Core Techniques
    • Week 9 Session 2: Advanced Prompting Strategies and Prompt Design Principles
  • Week 10: Building LLM-based Q&A Systems
    • Week 10 Session 1: Introduction to LLM-based Q&A Systems
    • Week 10 Session 2: Vector Databases and Embeddings
    • Week 10 Session 3: System Integration and Implementation
  • Week 11: Web Application Development Basics
    • Week 11 Session 1: Introduction to Web Development and Flask
    • Week 11 Session 2: Advanced Flask and Introduction to Streamlit
    • Week 11 Session 3: Integrating LLM APIs and Deployment
  • Week 12: Controlling and Structuring LLM Outputs
    • Week 12 Session 1: Fundamentals of LLM Output Structuring
    • Week 12 Session 2: Advanced LLM Output Control
    • Week 12 Session 3: Real-World LLM Applications

Projects

  • Team Project
  • NLP Project Proposal
  • Week [n] Project Research Note

About

  • Syllabus
  • Who made this book?
  • CHU AI Department
  • Repository
  • Open issue

Index

By Young Joon Lee

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