IE 7275 — Machine Learning and Data Analytics

4 semester hoursGraduateLectureusually offered: fall, spring, summerBostonOnlineSeattle, WAVancouver, CanadaLive CastOnlineTraditional

Covers the theory and applications of data mining in engineering. Reviews fundamentals and key concepts of data mining, discusses important data mining techniques, and presents algorithms for implementing these techniques. Specifically covers data mining techniques for data preprocessing, association rule extraction, classification, prediction, clustering, and complex data exploration. Discusses data mining applications in several areas, including manufacturing, healthcare, medicine, business, and other service sectors.

Prerequisites

Offering history

TermSectionsEnrolledCapacityFullOpen seats/section
Summer B 202322513019%52.5
Fall 202349815762%14.8
Spring 2024930739179%9.3
Summer A 202411205%19.0
Summer B 202411010010%90.0
Fall 202459313370%8.0
Spring 2025720971029%71.6
Summer A 2025154810%43.0
Fall 202549316058%16.8
Spring 2026412917872%12.3

Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.

Meeting times

Share of recent sections by weekday: M 17% · T 44% · W 32% · Th 22% · F 24%

Common patterns: T (25% of sections), W (13% of sections), TF (13% of sections), WF (11% of sections), MW (8% of sections), MR (8% of sections) — in patterns, R means Thursday

Professors

Fall

Spring

Summer A

Summer B

Percentages are each professor's average share of the season's enrolled students in recent terms.

Unlocks

DADS 7305, DS 5500, IE 7615

Courses that list IE 7275 in their prerequisites.

Links

Official catalog (IE course descriptions) · Student reviews on RateMyHusky · All IE courses · Plan it at numap.app