The program's core courses combine the disciplines of mathematics, statistics and computer science, (although you may be able to bypass certain core courses based on your prior education and experience).

After completing core course requirements, students:

  • Take elective courses in, or closely related to, the program's three discipline (a limited number of electives can be taken outside the department or even at other institutions, such as Carnegie Mellon and the University of Pittsburgh)
  • Complete an internship requirement, possibly through current employment
  • Optionally complete a faculty-directed capstone thesis or project

Learning Environment

Small classes are conducted in a supportive environment help you achieve your maximum potential.

Course scheduling is convenient for both full-time and part-time students.

Required Programming Languages

Most courses include a computational component, using:

  • MATLAB©, Maple (mathematics)
  • SAS©, R, JMP©, SPSS© (statistics)
  • Python, C++, Linux, Windows (computer science)

Programming languages, software and other computational tools evolve quickly and are often superseded by new versions. You will need to have a strong commitment to lifelong learning as technology in the computational sciences evolves.