MSBA 645

Data Mining

Data mining draws on statistics, artificial intelligence and machine learning to discover novel, interesting and actionable relationships and patterns in large and complex data sets. This course will introduce the student to the fundamentals of data mining, including methodology, data preparation, commonly used predictive models, supervised and unsupervised learning, model comparison and evaluation, and mining of unstructured data such as text. While the emphasis is on solving realistic business problems, the course will also provide a brief background for the various models and techniques introduced in the course. The course follows a learn-by-doing approach in which the students will complete assignments using real world data sets. A leading data-mining tool such as SAS Enterprise Miner will be used extensively in this course

Units: 3.0