ALY 3040 — Data Mining
3 semester hoursUndergraduateLectureusually offered: springOnlineOnline
Introduces the theories and tools for data mining techniques such as rule-based learning, decision trees, clustering, and association-rule mining. Also covers interpretation of the mined patterns using visualization techniques. Offers students an opportunity to gain the knowledge and experience to apply modern data-mining techniques for effective large-scale data pattern recognition and insight discovery. Introduces data analysis software—student teams evaluate, analyze, and report data for the methods used and insights discovered during case studies.
Prerequisites
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Spring 2026 | 1 | 6 | 30 | 20% | 24.0 |
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 0% · T 0% · W 0% · Th 0% · F 0%
Common patterns: async (100% of sections) — in patterns, R means Thursday
Professors
Spring
- Mohsen Bahrami (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Unlocks
Courses that list ALY 3040 in their prerequisites.
Links
Official catalog (ALY course descriptions) · All ALY courses · Plan it at numap.app