ISIT 337 Predictive Analytics • 5 Cr.
In this course students learn to go beyond simply querying data to do predictive data mining analysis. Students learn to apply data mining algorithms to realistic organizational data to find previously undiscovered patterns and draw conclusions. Students use current software tools and hands-on exercises to learn theoretical concepts. Prerequisite: ISIT 330 with a C or better.
After completing this class, students should be able to:
- Analyze the role of predictive analytics in an organization
- Analyze the differences between predictive analytics (data mining) and Data Query
- Analyze the nature of both supervised and unsupervised learning
- Create a variety of data mining models using predictive analytic software
- Select appropriate data mining techniques/algorithms for organizational needs
- Evaluate data mining models to assess their effectiveness
- Make predictions of future outcomes based upon data mining models
- Articulate the ethical issues surrounding data mining
- Spring 2019 (current quarter)