DATA MINING   [Archived Catalog]
2018-2019 Greensburg Campus Catalog


Minimum Credits: 3
Maximum Credits: 3
Introduction to data mining techniques, including data preprocessing, data mining primitives, association rules, decision trees, cluster analysis, classification and machine learning, data visualization, and data warehousing. Detailed applications from a wide variety of domains. It is a new elective course for IT and MIS majors. The hybrid designation means that the class will not be a run in the traditional way where students and instructor meet together for lectures and labs. There will be occasional in-person meetings, but the plan is for narrated PowerPoints for lectures and instruction scripts for labs to be posted to CourseWeb. Students will listen to lectures, complete homework and do lab work independently.
Academic Career: Undergraduate
Course Component: Lecture
Grade Component: Letter Grade
Course Requirements: PREQ: INFSCI 1022

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