Our partnership with the University of Massachusetts Dartmouth offers a dual-degree program in which students complete three years of undergraduate study in mathematics and data analytics at Salve Regina, followed by two years in UMass Dartmouth's graduate program in data science.
Explore a Rapidly Emerging Field
Data analytics and data science are fundamentally concerned with collecting, cleaning and analyzing raw information to identify patterns, draw conclusions, gain insights and support effective decision-making. Salve Regina's program provides a robust foundation in computer programming, data mining and machine learning, preparing students for leadership positions in data analytics, information management and knowledge engineering.
While at Salve Regina, students complete coursework in computer science, data science and analytics, mathematics, physics and statistics, along with Core Curriculum courses in the liberal arts. At UMass Dartmouth, they explore the rapidly emerging fields of data analytics and discovery informatics, which integrates mathematics and computer science to quantify and manipulate information in fields such as science, engineering, business, sociology, health care or planning.
Students who successfully complete the program earn a bachelor's degree in mathematics with a minor in data analytics from Salve Regina and a master's degree in data science from UMass Dartmouth.
Program Spotlight: UMass Dartmouth
UMass Dartmouth's data science program is jointly offered by the College of Arts and Sciences and the College of Engineering. The curriculum emphasizes the interdisciplinary nature of data science, with a focus on harnessing the potential power of big data to transform areas ranging from health care to business to government.
This is an emerging field that is impacting nearly all academic disciplines and industries. Fields such as health care, marine sciences, business management and political science – to name a few – are increasingly using data in more sophisticated ways to drive inquiry and decision making.
Dr. Scott Field, associate professor, UMass Dartmouth
In the classroom, our faculty - all of whom hold advanced degrees in mathematics or applied mathematics - help students hone their reasoning and problem-solving skills with a challenging curriculum that explores the fundamentals of mathematics, data science and analytics, statistics and computer science.
Life After Salve
The National Academy of Sciences, the National Association of Colleges and Employers, Business Insider and others cite data science among the fastest growing and highest paid career fields today. By 2040, it is likely that most jobs will require at least some basic data science skills, while millions of new jobs will become available to highly skilled data scientists, the NAS predicts. Business Insider reported data scientist as the best job in America based on recent surveys considering job satisfaction, job availability and median base salary.
Possible industries include:
- Business: Data analytics, product transactions and customer engagement
- E-commerce: Data aggregation, customer interactions, product sales data
- Finance: Personal banking, investment portfolios
- Government: Enabling research, mobile applications and data visualizations
- Health care: Digital health records, treatment effectiveness, patient health initiatives
- Social networking: User analytics for advertising and new applications
- Science: Analyze large amounts of data to form observations and conclusions
- Telecommunications: Data aggregation and service analytics
All in five years, students in this program acquire a highly respected, values-based liberal arts education, the flexibility and marketability of a B.A. in mathematics with a minor in data analytics, and a master's degree in data science – one of the fast-growing and highest paid professions.
Dr. Ernest Rothman, professor and chair, Department of Mathematical Sciences
Major in Mathematics (B.A.) and Minor in Data Analytics
- CSC103: Computer Programming I
- CSC104: Computer Programming II
- DSA201: Introduction to Data Science and Analytics
- DSA202: Data Analysis and Visualization
- MTH173: Discrete Mathematics
- MTH195: Calculus I
- MTH196: Calculus II
- MTH203: Calculus III
- MTH211: Linear Algebra
- MTH213: Differential Equations
- PHY205: Principles of Physics I
- PHY206: Principles of Physics II
Students entering the program in an odd calendar year complete the following three courses:
- MTH315: Geometry
- MTH411: Analysis I
- MTH412: Analysis II
Students entering the program in an even calendar year complete the following three courses:
- MTH421: Abstract Algebra
- STA341: Statistical Theory I
- STA342: Statistical Theory II
All students also choose one of the following:
- ACC405: Accounting Research and Analytics
- CSC300: Algorithms and Data Structures
- ECN307: Introduction to Econometrics