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Course Descriptions

The curriculum of the program in the Department of Mathematics is designed to provide a broad education in both theoretical and applied mathematics. It also develops the scientific knowledge and the problem solving, computing, and communications skills that are critical to a successful mathematically based career.

MA 384 - Data Mining

  • Credit Hours: 4R–0L–4C
  • Term Available: -
  • Graduate Studies Eligible: No
  • Prerequisites: MA 212, CSSE 120, and either MA 223 or MA 381
  • Corequisites: None

An introduction to data mining for large data sets, include data preparation, exploration, aggregation/reduction, and visualization. Elementary methods for classification, association, and cluster analysis are covered. Significant attention will be given to presenting and reporting data mining results. Same as CSSE 384.

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