Nov 20, 2018  
2017-2018 UMass Dartmouth Graduate Catalog 
2017-2018 UMass Dartmouth Graduate Catalog [Archived Catalog]

MS in Data Science

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The Data Science program, jointly offered by Computer Science in Engineering and Mathematics in Arts & Sciences, prepares students for leadership positionsin data analytics, information management, and knowledge engineering. Upon completing the program, graduates will have skills in computer programming, statistics, data mining, machine learning, data analysis and visualization that enable solving challenging problems involving large, diverse data sets from different application domains.

The Master of Science in Data Science will provide graduate students with advanced education and training in 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 (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.

This program is designed for professionals and organizational leaders who want to take on greater IT responsibilities and for people who want to transition into a career that uses computer information science to support decision making. The purpose of the program is to prepare students for employment in professional fields that require data analysis and representation, and a flexible, broad understanding of informatics. This program will appeal to students who want to learn technological and analysis tools used by leading science, engineering, business, academic, government and social organizations. Further, this program is designed to accommodate individuals with career or undergraduate degree in business, engineering, computer science, physical/life/social sciences, mathematics, liberal arts and education who desire to enhance their data analytics and information science skills and credentials


Program Goals

  1. Meet the growing regional and national demand for high-level information systems/science skills;
  2. Provide a path for individuals from diverse fields to rapidly transition to data science career paths;
  3. Enable established information technology and computing professionals to upgrade their technical management and development skills;
  4. Prepare graduates to apply data science techniques for knowledge discovery and dissemination to assist researchers or decision makers in achieving organizational objectives;
  5. Establish stronger ties to alumni to enhance opportunities for continued learning and leadership;
  6. Create innovators, entrepreneurs, business professionals who will lead the development of next generation information systems.


Learning Outcomes


At the time of graduation, students will:

  • be able 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;
  • have the ability to communicate their 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 better 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 bring them to bear to help others; 
  • have an appreciation for the professional, societal and ethical considerations of data collection and use


Program Steering Committee

Dr. Ramprasad Balasubramanian (COE/CIS)
Dr. Paul Bergstein (CIS)
Dr. Gary Davis (MTH) - Chair
Dr. Sigal Gottlieb (MTH)
Dr. David Koop (CIS)
Dr. Donghui Yan (MTH)


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