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Data Science
Graduate Certificate

The Data Science program, jointly offered by the Departments of Computer Science in the College of Engineering and Mathematics in the College of Arts & Sciences, prepares students for leadership positions in data analytics, information management, and knowledge engineering. 

The Data Science Graduate Certificate provides students with tools and training in data analytics and discovery informatics, which integrates mathematics and computer science for the quantification and manipulation of information from a cognate area of application (e.g., science, engineering, business, sociology, healthcare, planning). Emphasis is placed on merging strong foundations in information theory, mathematics, and computer science with current methodologies and tools to enable data-driven discovery, problem-solving, and decision-making.

With a graduate certificate in Data Science, you will:

  • develop skills in computer programming, data analysis, data mining, machine learning, statistics, and visualization
  • be prepared to solve challenging problems involving large, diverse data sets from different application domains
This certificate program is designed for students with an undergraduate background in science, technology, engineering, or mathematics who are looking to broaden their skillset with data science tools and techniques in data visualization, statistical analysis, and programming. Students can explore topics (e.g machine learning, high-performance computing, and building predictive models) that are most relevant to their career goals.

In addition, the Data Science Graduate Certificate is also designed to prepare students for employment in other professional fields that require data science. Individuals with a career or undergraduate degree in business, computer science, engineering, physical/life/social sciences, mathematics, liberal arts, and education who desire to enhance their data analytics and information science skills and credentials will benefit from this certificate program.

Graduate certificate in data science program goals

  • meet the growing regional and national demand for high-level information systems/science skills
  • provide a path for individuals from diverse fields to rapidly transition to data science career paths
  • enable established information technology and computing professionals to upgrade their 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

UMassD advantages

Bridge Program: For students who are not yet ready for the master of science degree program in data science, UMass Dartmouth offers a preparatory bridge program consisting of five courses in data science fundamentals. Offered through UMassD's Online & Continuing Education Programs, the preparatory curriculum is comprised of both online and in-person courses and may be completed within one year. Learn more

3+2 Program with Salve Regina University: UMass Dartmouth has partnered with Salve Regina University to develop a pathway for Salve Regina students to earn a bachelor’s degree in mathematics from their home school and a master’s degree in data science from UMass Dartmouth in just five years. Learn more.

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

University requirements for graduate admissions

  • Submit an application via the online portal. Be sure to provide your full legal name and to capitalize the first letter of all proper nouns.
  • Pay non-refundable $60 application fee (American Express, Discover, MasterCard or Visa) via the online portal. For Nursing applicants, the non-refundable application fee is $75.
  • Statement of Purpose, minimum 300 words. Unless otherwise indicated in the program requirement details, 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 us in making assistantship decisions.
  • Resume
  • Transcripts for all post-secondary institutions attended (regardless of whether a credential is earned or not). Unofficial transcripts are accepted for admissions application review, once enrolled a final official transcript is required. International students applying for Data Science must submit semester-by-semester transcripts as well as consolidated transcripts. 
  • Many programs have specific recommendations/requirements, please see the additional program-specific requirements for more information.
  • International students: official TOEFL, IELTS, Pearson PTE or Duolingo (if accepted by program) score. Unofficial scores are accepted for admissions application review, once enrolled official scores are required and must be sent by the testing agency (copies/scans not accepted). This is 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, see exemptions for more details. The Duolingo test is not accepted for the following programs: Art Education, Biology/Marine Biology, Luso-Afro-Brazilian Studies & Theory, Marine Science and Technology (MS, PSM, PhD), Nursing (MS, DNP, PhD), Portuguese Studies, Professional Writing and Communication, Psychology (ABA, Clinical, Research), and Public Policy.

Program deadlines

Data Science Faculty

Adam Hausknecht
Alfa Heryudono
Bo Dong
Cheng Wang
Donghui Yan
Firas Khatib
Gary Davis
Hua Fang
Haiping Xu
Iren Valova
Ming Shao
Ramprasad Balasubramanian
Scott Field
Sigal Gottlieb
Saeja Kim
Shelley Zhang
Yuchou Chang
Yanlai Chen
Zheng Chen