BUSIT 115 Data Mining I • 5 Cr.

Description

Introduces the computer-assisted process of evaluating enormous sets of data to find previously undiscovered patterns, draw conclusions and then make decisions based on these patterns. Concepts are introduced and hands-on exercises used to apply the concepts using current software tools. Prerequisite: BUSIT 105 with a C- or better.

Description starting Summer 2018

Introduces the computer-assisted process of evaluating enormous sets of data to find previously undiscovered patterns, draw conclusions and then make decisions based on these patterns. Concepts are introduced and hands-on exercises used to apply the concepts using current software tools. Prerequisite: BUSIT 105 with a C or better.

Outcomes

After completing this class, students should be able to:

  • Describe the role of data mining in an organization.
  • Describe the nature of both supervised and unsupervised learning.
  • Use Data Mining software to develop and apply data mining models.
  • Create, evaluate and apply Decision Tree models, then describe scenarios in which their use would be appropriate.
  • Create, evaluate and apply Unsupervised Clustering models, then describe scenarios in which their use would be appropriate.
  • Create, evaluate and apply Market Basket models, then describe scenarios in which their use would be appropriate.
  • Create, evaluate and apply basic time series models, then describe scenarios in which their use would be appropriate.
  • Describe ethical issues surrounding the use of data mining.

Offered