Since their introduction in 2017, Transformers have revolutionized Deep Learning, powering large language models (LLM) like ChatGPT and DeepSeek, image and video generation (e.g. Dall-E and Sora), and much more. In CS 25, one of Stanford's hottest seminar courses, we delve into Transformer architectures and their diverse applications through classroom discussions and instructor and guest lectures. Topics include LLM, creative uses in art and music, healthcare, neuroscience, robotics, and so forth. We host leading researchers, with past speakers like Andrej Karpathy, Geoffrey Hinton, Jim Fan, Ashish Vaswani, and folks from OpenAI, Anthropic, Google DeepMind, NVIDIA, etc. Lectures are livestreamed and recorded, attracting a global audience with over a million total YouTube views. This is a 1-unit S/NC course, where attendance is the only homework! Enroll via Axess or audit through livestreams or in-person, space permitting. Prerequisites: basic Deep Learning and Transformers knowledge (understanding of attention) or completion of CS 224N, CS 231N, or CS 230. Course website: https://web.stanford.edu/class/cs25/
1 units · Satisfactory/No Credit
Since their introduction in 2017, Transformers have revolutionized Deep Learning, powering large language models (LLM) like ChatGPT and DeepSeek, image and video generation (e.g. Dall-E and Sora), and much more. In CS25, one of Stanford's hottest seminar courses, we delve into Transformer architectures and their diverse applications through classroom discussions and instructor and guest lectures. Topics include LLM, creative uses in art and music, healthcare, neuroscience, robotics, and so forth. We host leading researchers, with past speakers like Andrej Karpathy, Geoffrey Hinton, Jim Fan, Ashish Vaswani, and folks from OpenAI, Anthropic, Google DeepMind, NVIDIA, etc. Lectures are livestreamed and recorded, attracting a global audience with over a million total YouTube views. This is a 1-unit S/NC course, where attendance is the only homework! Enroll via Axess or audit through livestreams or in-person, space permitting. Prerequisites: basic Deep Learning and Transformers knowledge (understanding of attention) or completion of CS224N, CS231N, or CS230. Course website: https://web.stanford.edu/class/cs25/
Offered in Spring 2027 at Stanford University.