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CSCI 581: Deep Learning

Computer Science · 4 credits

Covers the fundamentals of deep learning, including important models, such as deep feedforward, recurrent, convolutional and transformer neural networks, and algorithms and considerations for training them. The application of deep learning to domains such as natural language, speech and vision will also be discussed.

Offered in 6 of the 26 listed terms (Winter 2021 to Winter 2027).

Prerequisites

DATA 571

Prerequisite tree

Each course's own prerequisites, down to the first courses in the chain.

From Banner's catalog for Spring 2027. Banner lists only the requisites it enforces, so check the catalog entry too.

Required by (0)

No course lists it as a prerequisite.

Syllabi and course websites

None listed yet.

Instructors

InstructorSectionsTerms
Hutchinson, Brian6Winter 2021 to Winter 2027

Every offering in the listed terms (6 sections)

TermSecCRNTypeMeetsInstructorEnrolledDelivery
Winter 2027012289LectureMTWF 12:00pm-12:50pm · KB 307Hutchinson, Brian0/20Face to Face Instruction
Winter 2026012654LectureTR 12:00pm-1:40pm · AW 204Hutchinson, Brian16/15Face to Face Instruction
Winter 2025013444LectureTR 2:00pm-3:40pm · CF 420Hutchinson, Brian13/12Face to Face Instruction
Spring 2023023016LectureTR 10:00am-11:40am · CF 420Hutchinson, Brian10/9Face to Face Instruction
Spring 2022023583LectureMTWF 2:00pm-2:50pm · CF 420Hutchinson, Brian15/15Face to Face Instruction
Winter 2021013614LectureMTWF 12:00pm-12:50pm · REMOTE SYNCHutchinson, Brian12/10Face to Face Instruction