DATA 4270 - Predictive Analytics for Business

(3) Credit Hours

This course covers analytical modeling used to analyze current and historical data to understand and predict potential risks and opportunities for a business. The topics covered include various data mining models such as Discriminant Analysis, K Nearest Neighbor algorithm, Logistic Regression, Decision Trees, and Neural Networks. These techniques will be examined in the context of various business applications such as healthcare, marketing, finance, and retailing. Spring semester. Prerequisites: DATA 2140 and MATH 1830 with a C or better or Department Head approval. Junior standing. Differential course fee will be assessed.