COM SCI C260F
Foundation Models: Principles and Practice
Computer Science · 4 units · Graduate courses (200-299)
Discussion of advanced topics and state-of-the-art research in training foundation models, including large language models (LLMs) and large vision language models (LVLMs). Topics include pretraining and post-training foundation models, safety alignment, training reasoning LLMs and VLMs, and synthetic data generation for foundation models. Concurrently scheduled with course C160F.
Letter grading.
Requisites
Official UCLA wording
Requisite: course M146.
BruinTree reads · Prerequisite
confidence 1.00 · from UCLA’s structured dataRequires
Everything that has to come before this course, not just the courses named in the requisite above.
COM SCI C260F
- COM SCI M146Introduction to Machine Learning
- COM SCI 32Introduction to Computer Science II
- COM SCI 31Introduction to Computer Science I
- C&EE 110Introduction to Probability and Statistics for Engineers
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