BIA650 Data Mining for Decision Making (3 cr.)

Prerequisite(s): MBA618 , BIA630  
Supervised and unsupervised machine learning is explored. Discussion covers standard data mining techniques using machine learning algorithms, including correlation and association, discriminant analysis, and cluster analysis.

Upon completion of this course, students are expected to be able to do the following:

1. Comprehend the mechanics of machine learning, and multiple techniques such as pattern recognition, or statistical hypothesis testing.
2. Apply the data requirements for regressions, classification, and clustering machine learning activities.
3. Implement data cleansing, normalization, and standardization techniques.
4. Evaluate model accuracy and implement improvements.
5. Apply advanced modeling techniques to a variety of business activities.