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DATA 571: Machine Learning

Data Science · 4 credits · Computer Science

Key machine learning theory, algorithms and experimentation techniques. Generalization, bias and variance. Classification, regression, and clustering. Linear models and nonlinear models, including neural networks. Ethical issues in machine learning.

Offered in 4 of the 26 listed terms (Winter 2024 to Fall 2026).

Prerequisites

MATH 204 and MATH 341

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 (5)

CSCI 571, CSCI 573, CSCI 576, CSCI 581, CSCI 597H

What it leads to

Courses that list it as a prerequisite, then the courses that list those, 2 levels deep.

Syllabi and course websites

None listed yet.

Instructors

InstructorSectionsTerms
Hutchinson, Brian4Winter 2024 to Fall 2025
Morrison, Ezra1Fall 2026

Every offering in the listed terms (5 sections)

TermSecCRNTypeMeetsInstructorEnrolledDelivery
Fall 2026042419LectureMTWF 12:00pm-12:50pm · KB 311Morrison, Ezra10/20Face to Face Instruction
Fall 2025042750LectureMTWF 10:00am-10:50am · CF 125Hutchinson, Brian12/25Face to Face Instruction
Fall 2024043614LectureMTWF 12:00pm-12:50pm · CF 314Hutchinson, Brian3/10Face to Face Instruction
Winter 2024013950LectureMTWF 11:00am-11:50am · CF 316Hutchinson, Brian5/7Face to Face Instruction
Winter 2024013951LectureMTWF 12:00pm-12:50pm · CF 316Hutchinson, Brian10/12Face to Face Instruction