ISM 331

Data Mining and Reporting

Academic Year Semester Location Online
2018-2019 Fall, Spring Main campus No

Level: Undergraduate

Credits: 3

Lab Fee: None

Pre-requisites: ISM 301, BUS 322

Data mining is a class of analytical techniques that examine a large amount of data to discover new and valuable information. This course is designed to introduce the core concepts and tools of data mining, as well as the inplementaion of benefits, and outcome expectations. It will also identify industry branches which most benefit from data mining (such as retail, target marketing, fraud protection, healthcare and science, web and e-commerce). XL Minel or RapidMiner Data Mining Software will be used to mine real business datasets (in the public domain) and learn to extract knowledge. Various techniques are used and compared such as k-means Clustering, Linear and Logistical Regresiion, Neural Networks, Decsion Trees, Text and Web mining and OLAP retrieval. Prerequisites or corequisiste: ISM 301, BUS 322