The master's degree program in data science prepares you for leadership positions in data analytics, information management, and knowledge engineering. It is jointly offered by the departments of Computer Science in Engineering and Mathematics in Arts & Sciences.

With a master's degree in data science, you will:

  • develop skills in computer programming, statistics, data mining, machine learning, data analysis, and visualization
  • be prepared to solve challenging problems involving large, diverse data sets from different application domains
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You will explore the rapidly emerging fields of data analytics and discovery informatics—which integrates mathematics and computer science for the quantification and manipulation of information from a cognate area of application (such as science, engineering, business, sociology, healthcare, planning).

The program emphasizes:

  • strong foundations in information theory, mathematics, and computer science
  • current methodologies and tools to enable data-driven discovery, problem solving, and decision-making

Enhance your skills, advance your career

The program is designed for:

  • professionals and organizational leaders who want to take on greater IT responsibilities
  • individuals who aspire to careers using computer information science to support decision-making
  • students who want to learn technological and analysis tools used by leading science, engineering, business, academic, government, and social organizations

The MS in Data Science aims to:

  • meet the growing demand for high-level information systems/science skills
  • provide a path for individuals from diverse fields to rapidly transition to data science careers
  • enable established IT and computing professionals to upgrade technical management and development skills
  • prepare graduates to apply data science techniques for knowledge discovery and dissemination to assist researchers or decision-makers in achieving organizational objectives
  • create innovators, entrepreneurs, and business professionals who will lead the development of next generation information systems

At the time of graduation, students will:

  • be able to apply contemporary techniques for managing, mining, and analyzing big data across multiple disciplines
  • be able to use computation and computational thinking to gain new knowledge and to solve real-world problems of high complexity
  • be able to communicate ideas and findings persuasively in written, oral, and visual form and to work in a diverse team environment
  • apply advanced knowledge of computing and information systems applications to areas such as networking, database, security and privacy, and web technologies
  • be prepared for career advancement in all areas of information science and technology
  • be committed to continuous learning about emerging and innovative methods, technologies, and new ideas—and be able to use them to help others
  • appreciate the professional, societal, and ethical considerations of data collection and use

The program prepares you for careers that require data analysis and representation, and a broad, flexible understanding of informatics.

The MS in Data Science is a 30-credit program. You will arrange an individual graduate program with your advisor during the first semester, subject to approval by your Graduate Committee.

All students complete 3 required computer science courses and a master’s project course. Elective courses round out the program.

Program overview: MS in Data Science

Hands-on learning is crucial. You will have opportunities to:

  • participate in faculty-led projects
  • collaborate on industry, agency, and faculty-sponsored projects
  • pursue your own research interests

Faculty research is centered on data science across the disciplines: to treat disease, monitor neonate health, explore the universe, predict ocean turbulence, and solve complex numerical equations.

Center for Scientific Computing and Visualization Research (CSCVR): An interdisciplinary center where faculty and students collaborate using high-performance computers to address mathematical, engineering, physics, biology, chemistry, and oceanography computational issues and questions. Learn more about the CSCVR

The MS in Data Science is designed for individuals with career backgrounds or undergraduate degrees in business, engineering, computer science, physical/life/social sciences, mathematics, the liberal arts, and education who want to enhance their data analytics and information science skills and credentials.

Apply and submit all required application materials to the Office of Graduate Studies.

Required materials

  • Statement of purpose: 300 - 600 words. Indicate your graduate study objectives, research interests and experience, and business or industry experience if applicable. If you are applying for a teaching or research assistantship, include any special skills or experience that would assist in assistantship decisions.
  • Official transcripts: from all post-secondary institutions attended (regardless if a credential is earned or not). Transcripts should show class rank if available. Minimum requirements for admission are a 3.0 GPA (out of 4.0), although other evidence of professional competence can be considered for students who do not meet this criteria
  • Official GRE score: sent directly from ETS; copies/scans not accepted. Required except by those who are or are about to be graduates of the UMassD College of Engineering.
  • 3 letters of recommendation: from persons in the field of your academic major at the institution most recently attended or from supervisors familiar with your recent job performance. BS/MS applicants are encouraged to include a recommendation from a department faculty member willing to advise their graduate research.
  • Resume.

International students: official TOEFL or IELTS scores sent directly from ETS or testing agency; copies/scans not accepted. Required of any applicant who did not earn a bachelor’s degree or higher degree from an accredited academic institution in the U.S. or accepted English-speaking country.

Data Science Faculty

Contact

David Koop

Assistant Professor
Computer & Information Science
Dion 302E

508-910-6692
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Scott Field

Assistant Professor
Mathematics
Liberal Arts 394C

508-999-8318
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