CME 295 - Transformers & Large Language Models

This course explores the world of Transformers and Large Language Models (LLMs). You'll learn the evolution of NLP methods, the core components of the Transformer architecture, along with how they relate to LLMs as well as techniques to enhance model performance for real-world applications. Through a mix of theory and practical insights, this course will equip you with the knowledge to leverage LLMs effectively. Ideal for those with a background in calculus, linear algebra, and basic machine learning concepts.

CME 295 - Transformers & Large Language Models Syllabus Cheatsheet FAQ CME 295 - Transformers & Large Language Models This course explores the world of Transformers and Large Language Models (LLMs). You'll learn the evolution of NLP methods, the core components of the Transformer architecture, along with how they relate to LLMs as well as techniques to enhance model performance for real-world applications. Through a mix of theory and practical insights, this course will equip you with the knowledge to leverage LLMs effectively. Ideal for those with a background in calculus, linear algebra, and

saved by

• surya

related reading

• A Mathematical Framework for Transformer Circuitstransformer-circuits.pub
• Stanford CS336 | Language Modeling from Scratchcs336.stanford.edu
• Stanford CS25: Transformers United V6 I Overview of Transformersyoutube.com
• Advanced Topics in Natural Language Processingblender.cs.illinois.edu
• CSE 291 - AI Agents - UCSD CSEpearls-lab.github.io
• CS124 - From Languages to Information (Winter 2026)web.stanford.edu
• 6.S898 Deep Learning, Fall 2023phillipi.github.io
• Schedule - Large Language Models: Methods and Applications2024.cmu-llms.org
• Stanford CS349Ecs349e.github.io
• Fall 2026boazbk.github.io
• Transformer Explainer: LLM Transformer Model Visually Explainedpoloclub.github.io
• Stanford CS329A | Self-Improving AI Agentscs329a.stanford.edu