STATS 202: Data Mining and Analysis
Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining. Topics: decision trees, association rules, clustering, case based methods, and data visualization. Prereqs: Introductory courses in statistics or probability (e.g.,
Stats 60), linear algebra (e.g.,
Math 51), and computer programming (e.g.,
CS 105).
Terms: Aut, Sum
| Units: 3
Instructors:
Taylor, J. (PI)
;
Tran, L. (PI)
;
Cai, F. (TA)
;
Feldman, M. (TA)
;
GAO, Z. (TA)
;
Guo, K. (TA)
;
Han, K. (TA)
;
Markovic, J. (TA)
;
Miao, J. (TA)
;
Qian, J. (TA)
;
Ray, S. (TA)
;
Rosenbaum, A. (TA)
;
Tirlea, M. (TA)
;
Wang, X. (TA)
;
Wu, H. (TA)
STATS 202U: Data Mining and Analysis
For Summer UG Visitors only. Sames as
Stats 202. This course is offered remotely only via video segments. TAs will host remote weekly office hours using an online platform such as Zoom.
Terms: Sum
| Units: 3
Instructors:
Tran, L. (PI)
;
GAO, Z. (TA)
;
Han, K. (TA)
;
Miao, J. (TA)
;
Rosenbaum, A. (TA)
;
Tirlea, M. (TA)
;
Wang, X. (TA)
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