Earn your undergraduate degree in data science
At UMass Dartmouth, the data science major is an interdisciplinary, integrating mathematics and computer science with disciplines such as business, engineering, healthcare, planning, science, and sociology.
Data scientists manage, mine, and analyze big data across multiple disciplines—and use computational thinking to gain new knowledge and solve real-world problems of high complexity.
As a data science major, you’ll build a strong foundation in information theory and in the methods and tools of mathematics and computer science. You’ll gain skills in complex problem solving, data-driven discovery, decision support, machine learning, predictive and visual analytics, and statistics.
You’ll be prepared for leadership positions in data analytics, discovery informatics, information management, and knowledge engineering. Businesses, government, healthcare, and the natural and social sciences need more data scientists to explore and explain complex information.
For the BS in data science, you'll complete 73 credit hours in core data science courses, computer and information science, and mathematics. A total of 120 credits are required for the degree.
Offered jointly by the Computer Science Department and the Mathematics Department, the data science curriculum covers topics such as data visualization and matrix methods for data mining—as well as traditional courses in computer and information science and mathematics. Graduates will acquire skills in computer programming, statistics, data mining, machine learning, data analysis, and visualization needed to solve challenging problems involving large, diverse data sets.
During your senior year, you will complete a team capstone project that focuses on real-world, industry-specific challenges. Our students have classified gravitational wave signals, analyzed attendance patterns at NBA games, and classified and predicted the effectiveness of cancer drugs.
Learn more about the BS in Data Science program requirements.
Course descriptions, schedules and requirements
The minor in data science is designed for STEM-focused students looking to broaden their skillset with data science tools and techniques in data visualization, statistical analysis, and programming. Considering the growing importance of data science skills for the current and future workforce, a data science minor will complement a variety of majors including crime and justice, political science, business, psychology, biology, and physics, to name a few. Engineers of all types are also well suited for the data science minor. A total of 24-26 credits are required for the minor.
Median starting salary for data science majors, class of 2021:
AY 2021 NACE Data Collection of Undergraduate Alumni
According to Forbes magazine, data science is among the fastest-growing fields, with demand reaching nearly 700,000 job openings by 2020. Data scientists hold positions in business, government, healthcare, industry, the sciences, and occupational fields where they are needed to explore and explain complex information.
UMassD faculty and students play prominent role in probing the history of the universe.
- Capstone projects: most senior engineering students work in small teams on real-world, industry-specific challenges that demand analysis, proposals, prototypes, and solutions.
- Center for Scientific Computing & Visualization Research: Faculty and students collaborate on problems in science and engineering using high-performance computing.
- Internships & co-op: Gain hands-on experience that will be valuable to local, national, and global employers.
Expand your opportunities
- Accelerated BS/MS in Data Science: Continue your education at UMassD with an accelerated BS/MS degree program for qualified undergraduates that can be completed in five years.
- MS in Data Science: Prepare for leadership positions in data analytics, information management, and knowledge engineering.
- MS in Computer Science: Advanced study in theoretical computer science, computer systems, software engineering, parallel and distributed computing, and computer networks.
- PhD in Engineering & Applied Science: Emphasizes the interdisciplinary nature of modern research at the interfaces of engineering, the applied sciences, and technology.
- PhD in Mathematics Education: Prepares graduates for careers in education, scientific institutions, industries, and federal agencies.