Data Mining (4 Credits)

Learning Outcomes:

Critically evaluate the value and application of data mining for business and customer relationship management; Critically discuss the variety of methods constituting data mining including data analysis, statistical methods, machine learning and model validation techniques; Understand and apply the foundations of modeling approaches such as linear regression, linear classifiers, decision tree models and clustering; Communicate technically complex issues coherently and precisely

Topics:

1. Overview of data mining
2. Data visualization and pre-processing
3. Data mining in practice
4. Models and patterns
5. Introduction to data mining using SPSS and other software
6. Classification trees
7. Predictive modeling
8. Descriptive modeling
9. Classification models
10. Clustering