STAT 8240:Data Mining I

3 Class Hours 0 Laboratory Hours 3 Credit Hours
Prerequisite: Admission to the PhD program in Analytics and Data Science or Passing the assessment test offered by the Program Director of PhD in Analytics and Data Science
Data Mining is an information extraction activity whose goal is to discover hidden facts contained in databases and perform prediction and forecasting through interaction with the data. The process includes data selection, cleaning and coding, using statistical pattern recognition and machine learning techniques, and reporting and visualizing the generated structures. The course will cover all these issues and will illustrate the whole process by examples of practical applications. In addition to method applications, this course will also heavily focus on the theoretical understanding of statistical analysis and methods. Students are encouraged to use recent Data Mining software.