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Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: 1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary.

Machine perception is the ability of an embodied device to perceive, comprehend, and reason about the surrounding environment. This course will introduce students to foundational principles of geometric and statistical learning approaches for machine perception. Topics include sensing techniques (vision, motion, audio, touch), probabilistic state estimation, localization and mapping, 3D reconstruction, scene understanding, vision-language-action models. Students will implement, debug and test machine perception algorithms on different sensory data in Python through hands-on programming assignments. Prerequisite: CS225; one of CS441, CS446, CS445, or equivalent. Our goal is to attract more senior undergrads and offer a lecture-assignment-based course. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister.