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CSCI 481: 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 Spring 2027).

Prerequisites

DATA 371 or DATA 471

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, Brian5Winter 2021 to Winter 2026

Every offering in the listed terms (6 sections)

TermSecCRNTypeMeetsInstructorEnrolledDelivery
Spring 2027023277LectureMTWF 9:00am-9:50am · CF 420Staff0/35Face to Face Instruction
Winter 2026012653LectureTR 12:00pm-1:40pm · AW 204Hutchinson, Brian33/35Face to Face Instruction
Winter 2025013442LectureTR 2:00pm-3:40pm · CF 420Hutchinson, Brian18/23Face to Face Instruction
Spring 2023023015LectureTR 10:00am-11:40am · CF 420Hutchinson, Brian26/26Face to Face Instruction
Spring 2022023582LectureMTWF 2:00pm-2:50pm · CF 420Hutchinson, Brian21/20Face to Face Instruction
Winter 2021013593LectureMTWF 12:00pm-12:50pm · REMOTE SYNCHutchinson, Brian25/25Face to Face Instruction