| Proposal: | The College of Computer, Mathematical, and Natural Sciences proposes to establish a Master of Science in Data Science. This program exists currently as an iteration of the Master of Professional Studies (MPS) program. The 30-credit MPS program (titled Data Science and Analytics) has been in operation since the Winter 2019-2020 term. Master of Professional Studies programs were first approved in 2005, when the University System of Maryland Board of Regents and Maryland Higher Education Commission approved an expedited review process for master’s and graduate certificate programs that respond quickly to the changing market needs of working professionals. Once a new iteration of the MPS is approved through campus PCC review, it only needs approval by the USM Chancellor to become official.
A limitation of offering this program as an MPS iteration is that all Professional Studies programs must use the same generic Federal Classification of Instructional Programs (CIP) code, rather than a CIP code that accurately describes the program content. Those who search for academic programs by using the CIP codes related to Data Science will not find this program. Moreover,
some CIP codes are designated as “STEM” eligible by the US Department of Homeland Security, and international students with F1 visas who graduate from STEM designated programs may continue to work in the United States for two years longer than students in non-STEM designated programs. The generic CIP code for Professional Studies programs does not qualify as STEM designated, even if the academic content of the Professional Studies program is STEM-related, as is the case with this program.
Consequently, the college proposes to transition the current program from a Master of Professional Studies program to a stand alone Master of Science program in order for the program to be classified more accurately. The 30-credit curriculum will remain the same. The Master of Science in Data Science will provide students with an education in the theory and practice of data science including mathematical and statistical foundations, computational approaches, and communication considerations. In addition to the fundamentals of data science, the program covers data science-relevant probability and statistics, algorithms, big data systems, machine learning, data mining, and analysis of networks. The program consists of 10 required 3-
credit courses. The program is a non-thesis program and will have both an in-person and distanceeducation version. Students who finish the program successfully will be able to design, conduct, and interpret data analysis tasks. Students will be able to communicate data analysis findings and will be able to apply methods and tools of statistics, machine learning, and computer science to data studies.
The proposal was approved by the Graduate School PCC committee on September 27, 2023, and the Senate Programs, Curricula, and Courses committee on October 6, 2023. |
