MSAI3110
KNOWLEDGE DISCOVERY & DATA MIN
- Department
- Master of Sci in AI
- Terms offered
- 3
- Data refreshed
- Jun 27, 2026
Description
This course introduces students to the concepts and techniques of data mining, focusing on discovering patterns and knowledge from large datasets. Students will learn various data mining methods, including classification, clustering, association rule mining, anomaly detection, and predictive modeling. The course emphasizes practical applications of data mining in different industries, such as healthcare, finance, and marketing, using tools and programming languages like Python and R. Through handson exercises and real-world case studies, students will develop the skills needed to analyze complex datasets and derive actionable insights for decision-making.
Syllabi
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Offering history & forecast 2025–2026
| Year | Fall | Spring | Summer | Intersession |
|---|---|---|---|---|
| 2030 | 2030 Fall: not enough history to forecast. | 2030 Spring: not enough history to forecast. | 2030 Summer: 7% chance, medium confidence. Offered in 0 of 9 summer terms since 2018. | 2030 Intersession: 8% chance, medium confidence. Offered in 0 of 6 intersession terms since 2020. |
| 2029 | 2029 Fall: not enough history to forecast. | 2029 Spring: not enough history to forecast. | 2029 Summer: 6% chance, medium confidence. Offered in 0 of 10 summer terms since 2017. | 2029 Intersession: 7% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017. |
| 2028 | 2028 Fall: not enough history to forecast. | 2028 Spring: not enough history to forecast. | 2028 Summer: 5% chance, medium confidence. Offered in 0 of 11 summer terms since 2016. | 2028 Intersession: 7% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017. |
| 2027 | 2027 Fall: not enough history to forecast. | 2027 Spring: not enough history to forecast. | 2027 Summer: 5% chance, high confidence. Offered in 0 of 12 summer terms since 2015. | 2027 Intersession: 6% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017. |
| 2026 | 1 section | 1 section | Not offered | No data for this term |
| 2025 | 1 section | Not offered | Not offered | Not offered |
Future estimates combine recent offering frequency with detected multi-year cycles. Hover a cell for confidence and evidence; low-confidence estimates are marked with ~.
Meeting times
Most recent first- Sat, 9:00 AM–12:00 PM JC106 2026
- Sat, 9:00 AM–11:59 AM JC118 2026
- Wed, 6:30 PM–9:30 PM JC220 2025
| Term | Professor | Type | Credits | Enrollment | CRN |
|---|---|---|---|---|---|
| Fall 2026 | Salem B. Othman | Lecture | 1 | 6 of 30 enrolled | 24174 |
| Spring 2026 | Salem B. Othman | Lecture | 1 | 9 of 30 enrolled | 34601 |
| Fall 2025 | Salem B. Othman | Lecture | 1 | 32 of 30 enrolled | 24174 |