MGS 3701 / MKG 3950: Data Mining in Business

Undergraduate course on the data mining process and its business applications, from data preparation to predictive models.
Lecture
Undergraduate Course
Published

February 1, 2022

Keywords

data mining, predictive modeling, classification, clustering, R, Python

Course

  • Code and title: MGS 3701 / MKG 3950, Data Mining in Business
  • Level: Undergraduate
  • Institution: College of Business and Public Management, Wenzhou-Kean University

Terms taught

Spring 2022, Spring 2024, Spring 2025

What students learn

Data is among the most valuable strategic assets an organization holds, and data mining is the ongoing process of extracting information and patterns from it to support business decisions. The course makes students familiar with the data mining process and its applications from a managerial perspective, so that they can find information and knowledge in large data sets that answer business needs.

Topics

From the Spring 2022 course schedule:

  • Introduction and software installation
  • Overview of the data mining process
  • Data visualization and dimension reduction
  • Evaluating predictive performance
  • Multiple linear regression, k-nearest neighbors, the naive Bayes classifier
  • Classification and regression trees, logistic regression, neural nets, discriminant analysis
  • Ensembles and uplift modeling
  • Association rules and collaborative filtering; cluster analysis
  • Time series: regression-based forecasting and smoothing methods
  • Social network analytics and text mining
  • Cases, followed by a poster session

Alongside three exams, students write an individual proposal and data collection plan, then complete a team project with a report, code, data, and a web portfolio. The textbooks are the R and Python editions of Data Mining for Business Analytics (Shmueli et al.).

Tools

R, Python