The master of science in data science prepares students for positions in data science, analysis, and visualization. The program addresses the intersection of three areas driving data science: technologies, analytics, and business needs. Students completing the degree will manage data-driven decision-making and use, analyze, and evaluate technologies and techniques in an enterprise setting. Graduates will be able to design innovative solutions to data science challenges taking economic and societal interests into account. They will work in teams and communicate effectively leveraging networks and knowledge with ethical behavior. They will also manage projects and time effectively, respect and embrace diversity and cultures, and be flexible and adaptive.
A minimum of 30 credits must be completed to earn the master of science degree in data science. Of these, 21 credits are required by the core curriculum, 6 credits must be chosen from the list of elective courses, and 3 credits must be earned by taking either the Capstone or Internship course. Up to an additional 6 credits (for a total of up to 36 credits) will be required for students without a sufficient background in mathematics and/or programming:
- DSCI 6601 or equivalent is required for students without sufficient background in mathematics. A sufficient background entails sucessful completion of mathematically-intensive courses at the advanced undergraduate level with a grade of B or better from an accredited program.
- DSCI 6602 or equivalent is required for students without sufficient background in programming. Sufficient background can be demonstrated by coursework from an accredited program, or industry experience.
Final decisions on requirement for DSCI 6601 and/or 6602 are made on an individual basis, and may require successful completion of a placement exam.
Admission to the University of New Haven Graduate School requires that applicants hold a baccalaureate degree from a regionally-accredited U.S. institution or from a foreign institution that is recognized by its jurisdictional Ministry of Education for granting baccalaureate degrees. Admission decisions are based primarily on an applicant’s undergraduate record. Applicants must have a bachelor’s degree in engineering, computer science, information technology, mathematics, statistics, or science from an accredited institution. Applicants should have taken courses in statistics and databases or have proven experience in these areas. Applications will be strengthened by an overall undergraduate grade average of at least 3.0 (on a 4.0 scale). One goal of the program is to enroll a class with a diverse student body.
A prospective student who is currently completing undergraduate study should submit an official transcript complete to the date of application. In such cases, an admission decision may be made on the basis of a partial transcript, contingent upon completion of the baccalaureate degree. Registration is not permitted until a final, official transcript is submitted to the Graduate Enrollment Management Office.
Applicants for admission to the Graduate School must submit the following materials:
- A completed application form.
- Official transcript(s) from all colleges and universities attended.
- Official Graduate Record Exam (GRE) scores.
- Three letters of recommendation: letters should come from persons familiar with the applicant’s academic or work-related skills, performance, and promise. Typically, recommenders are current or former professors and/or employers.
- Personal statement: in the one- to two-page personal statement, applicants should address: 1) reasons for pursuing an advanced degree in the field of data science and 2) professional goals and how a degree from our program relates to those goals.