BUA 6210G - Data Mining

Credits: 4

This course offers students introduction to the fundamentals conceptual, operational and experiential aspects of automated data mining, focusing primarily on the use of pattern recognition algorithms to address common business problems involving classification and prediction. Supervised and unsupervised data mining approaches will be addressed in the context of the common data mining related challenges including dimensionality, regularization, overfitting and generalization. Various pattern and association rules and pattern discovery modes will also be addressed, including compressed, sequential and spatial patterns, as well as multi-level and multi-dimensional associations. Common data mining applications, including clustering and prediction will be discussed and illustrated.