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Course Details


CST 309 - DATA MINING

Methods of knowledge discovery in massive data, i.e. the study of computer-assisted process of digging through and analyzing enormous data sets and then extracting the "˜meaning' of the data by applying mathematical methods. The methods that we study in this course are designed to predict behaviors and future trends based on existing data. Topics include classifications techniques, clusterization techniques, association rule discovery techniques, techniques for improving data quality.

Credits: 3

Prerequisites:

  • MATH 300 (with a min grade of C-)
  • AND  MATH 217 (with a min grade of C-)
  •   OR  ACSC 300 (with a min grade of C-)
  •   OR  ACSC 347 (with a min grade of C-)
  •   OR  ECON 234 (with a min grade of C-)
  •   OR  MATH 347 (with a min grade of C-)
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    Course Notes:

    There are no additional notes for this course.