Multidisciplinary Studies, Data Science and Analytics Track, M.S.

Admission Requirements

  1. A bachelor’s degree from an accredited college or university with a minimum cumulative GPA of 2.5 (4.0 scale).
  2. A two- to three-page statement of intent (essay) that includes: educational and professional goals, relevant background experience, and reasons for interest in the Multidisciplinary Studies, Data Science and Analytics Track Program.
  3. Signed principal adviser consent form. Students in the DSA track will be advised by Dr. Joaquin Carbonara. 
  4. After the completed application is received the student will be contacted to set up an appointment for an interview with the director.

In addition, all applicants must review the Admission to a Graduate Program section in this catalog.

Program Requirements

  1. Completion of a minimum of 30 credit hours, comprising at least 15 hours of 600- and 700-level courses, including the master’s project.
  2. A maximum of 15 credit hours may be taken in a discipline that offers a master’s degree when the student does a master’s project (3 credits).
  3. A maximum of 18 credit hours may be taken in a discipline that does not offer a master’s degree.
  4. A maximum of 15 credit hours may be taken at another accredited institution. This coursework must conform to the limitations stated in 2 and 3 (above), meet the requirements of the Transfer Credit policy, and have the prior approval of the principal adviser.  
  5. Only grades of B or better will be accepted as transfer credit. An official transcript showing transfer credit must be submitted to the Graduate Studies Office.
  6. Coursework (including transfer credit) must be completed within the six-year period immediately preceding the date of completion of the program.
  7. A maximum of 6 credit hours of independent study may be included in the program.
  8. Students must maintain a minimum cumulative GPA of 3.0 (4.0 scale).
  9. Master of Science candidates must complete a) a research methods course and b) a supervised project approved by the principal adviser.  Individual principal advisers may impose further requirements on candidates based on practices and policies of their home department (second reader or oral defense, for example). These must be specified in writing at the outset of the degree program on the completed Principal Adviser Consent Form.
  10. Degree Candidacy Application Form, approved by the student’s principal, secondary (if required), and tertiary (if required) must be submitted to the director before the completion of 12 credit hours at Buffalo State.
  11. Students completing degree requirements each spring semester are requested to    submit designated assignments/artifacts in Taskstream by the close of the semester for the Multidisciplinary Studies Program Assessment.
Required Courses (12 credit hours)
Computer Science (6 credit hours)
CIS 512INTRODUCTION TO DATA SCIENCE AND ANALYTICS3
CIS 600MACHINE LEARNING FOR DATA SCIENCE3
Mathematics and Statistics (6 credit hours)
MAT 646INTRODUCTION TO STATISTICS FOR DATA SCIENCE3
MAT 616ELEMENTS OF MATHEMATICS, PROGRAMMING AND COMPUTER SCIENCE FOR DATA SCIENCE3
Electives (12 credit hours)
Select 12 credit hours from the following:12
DATA ORIENTED COMPUTING AND ANALYTICS
MACHINE LEARNING MODELS IN PYTHON
DATABASES AND THE DATA SCIENCE INFORMATION LIFE CYCLE
DATA STRATEGY AND GOVERNANCE
COMMUNICATION FOR LEADERS AND MANAGERS
GEOSPATIAL PROGRAMMING
PROJECT MANAGEMENT FOR MATH AND SCIENCE PROFESSIONALS
COMMUNICATION STRATEGIES FOR MATH AND SCIENCE PROFESSIONALS
Other courses available with advisement
Research Methods and Internship (6 credit hours)6
DATA STRATEGY AND GOVERNANCE
OR
PROJECT MANAGEMENT FOR MATH AND SCIENCE PROFESSIONALS
OR
COMMUNICATION STRATEGIES FOR MATH AND SCIENCE PROFESSIONALS
MASTER'S PROJECT
Total Credit Hours30

Students will:

  1. Demonstrate effective and appropriate communication skills through coherent and well-organized written presentations.
  2. Demonstrate effective and appropriate communication skills through coherent and well-organized oral and visual presentations.
  3. Demonstrate the ability to creatively use information, concepts, analytical approaches, and critical thinking skills in one or more disciplines. Competency in making connections that will synthesize and transfer learning to new and complex situations.
  4. Ethically identify, access, critically evaluate, and apply information throughout collections of work.
  5. Demonstrate a basic knowledge of research design, methodology, and measurement strategies that addresses a problem in the field.
  6. Demonstrate analytical skills through self-reflection to assess individual performances or collections of work. Show evidence of personal, professional, and civic engagement/development.