The University offers a Master of Science (M.S.) in the area of data science & analytics. The MS in Data Science & Analytics includes core knowledge and specialized elective areas. This graduate program provides the student with a strong background needed to pursue a career in academic research, government and industrial research, marketing, logistics, and actuarial work.
The program is specialized to fit the individual needs and plans of each student. Specific objectives of the program are the following.
To provide the student with experience with ‘big data’. Original research and/or internships are the single most important requirements leading to the M.S. degree.
To provide the student with specialized, in-depth training in their chosen emphasis area -- Aviation Logistics, Bioinformatics, Business Analytics, Computational Science, or Criminology and Criminal Justice.
The following provides a brief overview of the admission and degree requirements for the program as a whole and each concentration within the degree.
Admission to the M.S. Program
In addition to the requirements of the School of Graduate and Professional Studies for admission, applicants are expected to have coursework or equivalent experience in introductory statistics, introductory computer programming, differential and integral calculus, and matrix algebra. Students with deficiencies can be granted conditional admission. Deficiencies must be removed by taking appropriate courses or directed study; these credit hours do not apply to the number of required hours for the graduate degree. Prospective students should submit (a) official transcripts, (b) a resume or curriculum vitae, (c) scores on the General Tests of the Graduate Record Examinations (GRE) or Graduate Management Admission Test (GMAT), and (d) contact information for three references.
Incoming students with deficiencies shall be placed into the following courses (or an equivalent course) - introductory statistics - MATH 241 Principles of Statistics; computer programming - CS 151 Introduction to Programming; differential calculus - MATH 131 Calculus I; integral calculus - MATH 132 Calculus II; matrix algebra - Math & CS department matrix algebra quick start.