Stanford CS324: Large Language Models
FreeStanford's deep dive into large language models: theory, practice, and ethics
FreeFree tier
About Stanford CS324: Large Language Models
Stanford CS324 is a graduate-level course that provides a comprehensive introduction to large language models (LLMs). The curriculum covers the fundamentals of modeling, theory, ethics, and systems aspects of LLMs, with hands-on projects that involve evaluating models like GPT-3 and building models like BERT. The course features lectures, paper discussions, and student-led panels, aiming to give students both theoretical understanding and practical experience in working with state-of-the-art language models.
Key Features
Covers modeling, theory, ethics, and systems of large language models
Hands-on projects: evaluate models like GPT-3 and build models like BERT
Lectures with detailed lecture notes available online
Paper discussions and student-led panels on required readings
Access to state-of-the-art language models for project work
Pros & Cons
Pros
- Comprehensive curriculum covering both theory and practical aspects
- Free access to lecture notes and course materials
- Hands-on projects with real models like GPT-3 and BERT
- Taught by leading Stanford faculty (Percy Liang, Tatsunori Hashimoto, Christopher Ré)
- Includes discussion panels for deeper engagement with research papers
Cons
- Course is not a standalone AI tool but an educational resource
- Full participation requires Stanford enrollment or access to Canvas/Gradescope
- Content may be dated as the course was held in Winter 2022
- No ongoing updates or support beyond the course period
Best For
Learning the fundamentals of large language modelsConducting critical evaluation of language model capabilities and risksGaining hands-on experience training and fine-tuning language modelsExploring ethical and scalability challenges of LLMsPreparing for research or engineering roles in NLP and AI
FAQ
What is Stanford CS324?
Stanford CS324 is a graduate course on Large Language Models, covering modeling, theory, ethics, and systems. It includes lectures, paper discussions, and hands-on projects.
Is the course free to access?
The lecture notes and some materials are freely available on the course website. However, full participation (quizzes, projects, grading) requires Stanford enrollment.
What models are used in the projects?
Students get access to models such as GPT-3 for evaluation projects and can train models like BERT-base for building projects.
Who teaches the course?
The course is taught by instructors Percy Liang, Tatsunori Hashimoto, and Christopher Ré, with course assistants Rishi Bommasani and Sang Michael Xie.