Dartmouth College

What you'll study

The Data Science major at Dartmouth integrates core computational and statistical foundations with applied coursework and a project-based capstone. Core topics typically include programming and software design, calculus and linear algebra, probability and statistical inference, data structures and algorithms, databases, and introductory machine learning. Students also study data visualisation, experimental design, ethics and privacy in data, and computational modelling.

The programme is structured to balance required core courses with electives drawn from computer science, statistics, mathematics and domain areas such as economics, biology, public policy or engineering. Many students take advantage of interdisciplinary offerings and Thayer School collaborations to pursue courses in scientific computing, signal processing, optimisation, or applied machine learning. A culminating experience—often a senior thesis or practicum—gives students the opportunity to apply methods to an open-ended research or real-world problem, frequently working with faculty, research groups or external partners.

Entry requirements

Dartmouth seeks applicants with strong quantitative preparation and demonstrated intellectual curiosity. Typical preparation includes higher-level secondary courses in mathematics (calculus and/or statistics) and some background in programming or computational thinking. Admissions decisions are holistic and consider secondary-school grades, letters of recommendation, personal essays, and extracurricular experiences; standardised tests may be optional or considered as one element among many.

For transfer or internal applicants, competitive preparation generally includes college-level coursework in calculus, linear algebra, introductory computer science and statistics, along with evidence of success in quantitative subjects. International applicants should present the equivalent rigour in their national systems and provide any required English-language proficiency documentation.

Career prospects

Graduates with a Dartmouth Data Science degree pursue a broad range of careers where data and computation are central. Common entry roles include data analyst, data scientist, machine learning engineer, software engineer with a data focus, business intelligence analyst and research assistant. Because the curriculum emphasises application and communication, alumni also move into product management, consulting, policy roles that require quantitative analysis, and roles within health analytics or biotech when combined with domain electives.

Many students continue on to graduate study in statistics, computer science, engineering, business analytics or public policy. The programme’s emphasis on a sizeable capstone or thesis, undergraduate research opportunities and internship experience helps graduates demonstrate practical skills to employers and graduate programmes.

Why study at Dartmouth College

Dartmouth combines a liberal-arts undergraduate environment with strong strengths in computing and engineering through collaborations with the Department of Computer Science, the Department of Mathematics, and the Thayer School of Engineering. Students benefit from small class sizes and easy access to faculty, enabling close mentorship on research projects and senior theses.

The college encourages interdisciplinary study, so Data Science majors can combine technical training with coursework across the social sciences, natural sciences and humanities. Hands-on learning is emphasised through practicum courses, undergraduate research, internships facilitated by career services and an active alumni network. Finally, Dartmouth’s campus culture and research centres provide opportunities to work on real-world problems in areas such as healthcare analytics, environmental modelling, social-data research and computational biology.