Data Analytics - M.S.

The Data Analytics Master of Science degree program is designed to provide students with in-depth knowledge for applying statistical methods and tools to solve real-world problems using data. The program includes core courses in statistical topics as well as advanced applications of data analytics. Students delve into the areas of data mining, analytics, management and visualization, forecasting, modeling, and optimization and simulation which provide skills necessary to fill the current analytics gap and prepare students for both the technical and business challenges posed by big data.

Upon completion of the program, graduates are expected to:

  • Integrate the knowledge of mathematics, statistics and computer science to collect, analyze and interpret data.
  • Use data to drive organizational decisions and optimize performance.  
  • Conduct analysis for advanced data mining strategies to optimize model performance.
  • Make recommendations based on the evaluation of the ethical, legal and political issues of data usage and its implications for a given application, market or population.

Data Analytics

Master of Science

Prerequisite Courses *
FIT1040Spreadsheet Design for Business Solutions (or passing grade on challenge exam)3
Core Courses
DATA5025Tools for Data Analytics3
DATA5050Data Management3
DATA5100Statistical Analysis3
DATA5150Data Mining3
DATA5200Data Visualization3
DATA5300Big Data Analytics3
DATA5350Text & Web Mining Analytics3
DATA5400Introduction to Predictive Modeling3
DATA5515Advanced Topics in Predictive Analytics3
DATA5550Optimization Simulation3
DATA5600Research Methods in Data Analytics3
DATA5700Data Analytics Capstone3
Total Credits36.0-39.0

Prerequisite courses must be completed prior to or concurrently with core courses.