DTM 535 - Data Mining and Knowledge Management

Institution:

Thomas Edison State University

Subject:

Data Management and Analytics

Description:

This course will serve to introduce students to data mining and knowledge management. Data mining (DM) is concerned with the discovery of ""hidden"" knowledge in large data sets. This knowledge represents one aspect of an organization's intellectual capital and is often expressed in the form of trends or major themes that reoccur in the data. Knowledge management (KM) systems are designed to exploit the results of data mining and facilitate the analysis and evaluation of both tangible and intangible knowledge assets. In this course students will explore data mining methods used for prediction and knowledge discovery. These methods include regression, nearest neighbor, clustering, K-means, decision trees, association rules, and neural networks. In addition, students will become familiar with the current theories, practices, tools, and techniques used to management knowledge assets.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.tesu.edu

Phone Number:

(609) 984-1100

Regional Accreditation:

Middle States Association of Colleges and Schools

Calendar System:

Semester

The Course Profile information is provided and updated by third parties including the respective institutions. While the institutions are able to update their information at any time, the information is not independently validated, and no party associated with this website can accept responsibility for its accuracy.