CSCI 5942: AI Engineering (Fall 2026)

Engineers and analyzes the trade-offs in large-scale AI systems. This course connects model architecture design with the practical, distributed systems required to train and serve them. Covers the full engineering lifecycle, including data curation, distributed training, inference optimization, and scaling large language models. Recommended prerequisite: strong programming proficiency in Python, experience with a modern ML framework (eg, PyTorch), and proficiency with git and command-line environments.

Lectures: Tuesday/Thursday, 2:00PM-3:15PM, Miramontes Baca Education Bldg 155
Communications: Piazza (TBD)
Assignment Submission: Gradescope (TBD)
Course Notes: Canvas (TBD)

Instructors

Christoffer Heckman

Office Hours: TBD.
ARPG Research Group

Mark Zhao

Office Hours: TBD, or by appointment. ECCR 1B26, Engineering Center.
BASIL Research Group

TAs/Course Staff

TBD