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Fall 2013 Statistics W3026 section 001 APPLIED DATA MINING | |
| Call Number | 77702 |
| Day & Time Location |
MW 10:10am-11:25am To be announced |
| Points | 3 |
| Approvals Required | None |
| Instructor | Shawn E Simpson |
| Type | LECTURE |
| Course Description | Data Mining is a dynamic and fast growing field at the interface of Statistics and Computer Science. The emergence of massive datasets containing millions or even billions of observations provides the primary impetus for the field. Such datasets arise, for instance, in large-scale retailing, telecommunications, astronomy, computational and statistical challenges. This course will provide an overview of current practice in data mining. Specific topics covered with include databases and data warehousing, exploratory data analysis and visualization, descriptive modeling, predictive modeling, pattern and rule discovery, text mining, Bayesian data mining, and causal inference. The use of statistical software will be emphasized. |
| Web Site | CourseWorks |
| Department | Statistics |
| Enrollment | 41 students (75 max) as of 11:19PM Wednesday, May 22, 2013 |
| Subject | Statistics |
| Number | W3026 |
| Section | 001 |
| Division | Interfaculty |
| Open To | Columbia College, Engineering and Applied Science, General Studies, School of Continuing Education, Graduate School of Arts and Science, School of the Arts, International and Public Affairs, Barnard, Engineering and Applied Science: Graduate |
| Campus | Morningside |
| Section key | 20133STAT3026W001 |
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