MAT 303 Introduction to Data Mining
This course covers motivations behind Data Mining, exploring its uses and abuses in modern society, and applying some elementary techniques to real-world data sets such as Data Preprocessing, Classification, Association Analysis, Clustering, and Dimension/Noise Reduction. The course will culminate in an extensive exploratory project. As a Capital Designated Course, students will also use knowledge and techniques gained from their previous classes to: connect examples, facts, or theories from more than one content area; connect knowledge (facts, theories, etc.) from general education coursework to civic engagement and to the student's participation in civic life and/or community or professional contexts and structures. Prerequisites: Completion of
MAT-203 with a minimum grade of B, and one course from:
MAT 230, 231, or
CS 110. Capital designated course.
Prerequisite
Completion of
MAT 203 with a grade of B or higher and one course from: MAT 210, 222, or
CS 110.