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Course Details


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


There are no prerequisites listed for this course.

Course Notes:

Prerequisites: Math/ASCS 300with a min grade of C- and

(Math 217 or Econ 234 or Math 347 or ACSC 347

with a min grade of C-).