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COURSE INFORMATION

COURSE TITLE Introduction to Data Mining
CREDIT RANGE 4.000
SCHOOL Seidenberg School of CSIS
DEPARTMENT Computer Science 
LEVEL Undergraduate
COREQUISITE none
PREREQUISITE CS 241 Minimum Grade of D
DESCRIPTION:

Course Description: This course will provide an overview of topics such as introduction to data mining and knowledge history; data mining with structured and unstructured data; foundations of pattern clustering; clustering paradigms; clustering for data mining; data mining using neural networks and genetic algorithms; fast discovery of association rules; applications of data mining to pattern classification; and feature selection. The goal of this course is to introduce students to current machine learning and related data mining methods. It is intended to provide enough background to allow students to apply machine learning and data mining techniques to learning problems in a variety of application areas.

Course Rotation: Fall.



SECTION INFORMATION

CRN: 50370
SUBJECT: CS
COURSE NUMBER: 325
SECTION TITLE: Introduction to Data Mining
CAMPUS: Online
SCHEDULE TYPE: Lecture
REQUIRED MATERIAL: To Be Determined
SECTION COMMENTS: This is an online section that requires online participation and attendance via Blackboard.
COREQUISITE None
FEES: 0
CAPACITY 10
SEATS AVAILABLE 10
INSTRUCTOR: David Benjamin
RESTRICTION(S):

Online

Online Type Date
BlackBoard 07/15/2019 - 08/24/2019