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CSCI 477: Data Mining

Computer Science · 4 credits

Techniques for extracting useful information from large data sets; attribute-value learning techniques (decision trees, association rules); relational mining techniques (inductive logic programming, efficient search of relational spaces); probabilistic techniques (Bayesian networks, conditional independence); statistical techniques; sampling strategies; applications in bioinformatics, personalization, information retrieval, web modeling, filtering, and text processing.

Offered in 3 of the 26 listed terms (Spring 2022 to Fall 2024).

Prerequisites

MATH 204 and MATH 341 and CSCI 305

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
Hearne, James2Spring 2022 to Spring 2023
Tuor, Aaron1Fall 2024

Every offering in the listed terms (3 sections)

TermSecCRNTypeMeetsInstructorEnrolledDelivery
Fall 2024043601LectureMTWF 11:00am-11:50am · BH 317Tuor, Aaron11/35Face to Face Instruction
Spring 2023024008LectureTR 2:00pm-3:40pm · ES 413Hearne, James17/20Face to Face Instruction
Spring 2022023962LectureMTWF 1:00pm-1:50pm · AW 203Hearne, James34/35Face to Face Instruction