Department

Management Information Systems

Course Code

MIS 522

Course Title

Knowledge Management and Data Mining

Course Credit

3

Prerequisite Course

Course Level

second Year

Course Description

This course will cover data mining for business intelligence. Data mining refers to extracting or “mining” knowledge from large amounts of data. It consists of several techniques that aim at discovering rich and interesting patterns that can bring value or “business intelligence” to organizations. Examples of such patterns include fraud detection, consumer behavior, and credit approval. The course will cover the most important data mining techniques:  classification, clustering, association rule mining, visualization, prediction ;through a hands-on approach using XL Miner and other specialized software, such as the open-source WEKA software.

Course Material

Irma Becerra-Fernandez, Avelino Gonzalez, Rajiv Sabherwal (2004). Knowledge Management Challenges, Solutions, and Technologies (edition with accompanying CD). Prentice Hall. ISBN: 0-13-109931-0.

Reading Recommendation

Pang-Ning Tan, Michael Steinbach, Vipin Kumar (2005). Introduction to Data Mining. Addison-Wesley. ISBN-10: 0321321367

Official website of the course on the learning management system: LMS.ksu.edu.sa

Course Language

English