Approaches, techniques and tools for data analysis and knowledge discovery. Introduction to machine learning, data mining, and the knowledge discovery process; data storage including database management systems, data warehousing, and OLAP; testing and verification methodologies; data preprocessing including missing data imputation and discretization; supervised learning including decision trees, Bayesian classification and networks, support vector machines, and ensemble methods; unsupervised learning methods including association mining and clustering; information retrieval.
Section | Capacity | Class times | Login to view Instructor(s) and Location |
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LECTURE B01
(88955) |
25 |
2026-01-05 - 2026-04-10 (MW)
11:00 - 12:20
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Section | Capacity | Class times | Login to view Instructor(s) and Location |
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SEMINAR 800
(89017) |
25 |
2026-01-05 - 2026-04-10 (T)
14:00 - 14:50
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