College of Information Sciences and Technology

This option focuses on the principles, methods, and tools for management, integration, analysis, visualization, and predictive modeling of massive, complex, data. Students in this option will master the principles underlying modern data analytics and machine learning methods. Hands-on labs and projects with real-world datasets provide students with the Data Sciences knowledge and skills needed to develop, apply, and validate machine learning solutions to extract actionable knowledge from massive data sets across multiple application areas (e.g., health, education, security).

In addition to the courses shared with other Data Sciences options, students in this option must complete IST’s general introductory course Information, Technology and People and an approved internship. In addition they will complete five courses that will expand their ability to apply data sciences concepts and methods (Introduction to Data Sciences; Machine Learning for Data Sciences; Data Integration and Fusion; Visual Analytics for Data Sciences; Data Analytics at Scale).

Students in this option will also make selections from several lists designed to expose the students to a broad set of issues related to data science applications. For example, some of these courses provide experience with specific domains of big data (e.g., biology and human development, astrophysics, cognitive science, digital libraries, or political science). In total these selections will comprise 18 credits toward the degree. A detailed listing of these requirements and of the approved course lists can be found at