Masters in Data Analytics
Master of Science
The M.S. degree in Data Analytics (MSDA) is offered in on-campus, online, and blended formats. On-ground students will have the option of taking online or blended classes as well. The degree aims at providing an interdisciplinary approach to data analytics that covers both the foundational mathematical knowledge of data science and the computational methods and tools for preprocessing, interpreting, analyzing, representing, and visualizing data sets. Applicants to the online MSDA degree are accepted each fall semester. The Data Analytics program may, at its own discretion, accept new students in other semesters.
Contact and Application
To be fully admitted to the Master of Science in Data Analytics program, students must have completed a bachelor’s degree with a minimum GPA of 3.0 on a 4.0 scale, and have completed all prerequisite courses (below) with a grade of B- or better.
MAT 113 (Business Calculus) or MAT 115 (Calculus I)
MAT 121 Applied Statistics
CSC 302 Discrete Structures (4 hrs)
CSC 225 Computer Programming Concepts I
CSC 275 Computer Programming Concepts II
CSC 385 Data Structures and Algorithms
DAT 332-Matrix Analysis and Numerical Optimization (or MAT 332)
All applicants must provide written evidence of their ability to perform at a high academic level by submitting a personal and academic statement.
A GRE score is not required for admission to the Master of Science in Data Analytics program.
Students who have not yet completed all prerequisites may be granted conditional admission; this allows them to work on up to 12 hours toward the degree. Grades of B- or better must be earned in all courses.
Apply through UIS Admissions to the Master’s in Data Analytics program today
Note: After acceptance, and before signing up for any of the currently offered DAT classes, contact Dr. Nguyen (above) for help in choosing the correct classes.
Potential career paths for this major:
Data Scientist (ranks very high in both growth outlook and median income–see Forbes April 2016)
Big data developer
Market research analysts
Operations research analysts
Healthcare quality analysts
Medical drug trial analysts
Information security analysts
Social networking data analysts
Environmental data specialists
Graduates of the program will have a foundation in Data Analytics that will prepare students for a professional career or entry to a Ph.D. program”.