Select the desired Level or Schedule Type to find available classes for the course. |
DSCI 401 - Data Mining (3). |
Description: This course will provide a broad overview of data mining concepts, methodologies, implementation techniques, and programming. It will include fundamental topics such as decision trees and random forests, association rule mining, clustering, advanced regression techniques, Bayesian methods, and neural networks. Additional topics may include data cleaning and techniques for text and web mining.
Prerequisite: DSCI 201, CSCI 208, and MATH 544.
Notes: Offered in fall.
3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate Schedule Types: Independent Study/Research, Lecture Mathematics Department Prerequisites: Prereq for DSCI 401 General Requirements: Course or Test: CSCI 208 Minimum Grade of D- May not be taken concurrently. and Course or Test: DSCI 210 Minimum Grade of D- May not be taken concurrently. and Course or Test: MATH 544 Minimum Grade of D- May not be taken concurrently. |
Return to Previous | New Search |