CIS 435-0
( Elective ) Introduction to Data Warehousing and Data Mining
This course provides an introduction to data mining, with a few hours of focus on data warehousing as one of the commonly used data sources for data-mining applications. Students learn data-mining applications, core concepts, and algorithms. Among these algorithms are supervised (Naive Bayes, Decision Tree, and Neural Network) and non supervised (Association Rules, commonly used for market basket analysis, and Clustering) algorithms. Students learn via experimentation; they observe the outcome of applying data mining algorithms to real-life data. Part of the Database and Internet Technologies specialization. Prerequisite: CIS 317. The online version of this course is only for students in the MMI Online program.
