— Generative AI & Large Language Models
Generative modeling techniques and architectures for large-scale AI systems, focusing on large language models (LLMs) and multimodal generative models. Transformer architectures, pretraining and fine-tuning, instruction following, in-context learning, alignment and safety, and applications to text generation, code, dialogue, and retrieval-augmented generation. Theoretical and practical implementation, evaluation, limitations, and societal impacts of generative AI.
Prerequisites & course information
Course Description: Generative modeling techniques and architectures for large-scale AI systems, focusing on large language models (LLMs) and multimodal generative models. Transformer architectures, pretraining and fine-tuning, instruction following, in-context learning, alignment and safety, and applications to text generation, code, dialogue, and retrieval-augmented generation. Theoretical and practical implementation, evaluation, limitations, and societal impacts of generative AI. Learning Activities: Lecture 3 hour(s), Project. Enrollment Restriction(s): Open to graduate students in Computer Science only. Grade Mode: Letter. This course version is effective from, and including: Fall Quarter 2026. Learning Activities: Lecture 3 hour(s), Project. Enrollment Restriction(s): Open to graduate students in Computer Science only. Grade Mode: Letter.
Sources
- Course catalogue ↗2026-2027