Marymount University

What you'll study

The programme builds a strong foundation in core mathematics while emphasising computational techniques and applications. Core coursework typically includes calculus sequence, linear algebra, differential equations, real analysis, discrete mathematics and probability and statistics. Computational and applied topics include numerical analysis, scientific computing, mathematical modelling, algorithms, and data structures, together with programming courses using languages and tools common in industry (for example Python, MATLAB, or similar).

Students generally complete a combination of required mathematics courses, concentration electives in computational mathematics, and supporting courses in computer science and statistics. The curriculum commonly culminates in a capstone experience — such as a senior project, applied research with a faculty mentor, or an internship — where students apply mathematical modelling and computational methods to a substantive problem.

• Core mathematical theory: calculus, linear algebra, real analysis
• Computational methods: numerical analysis, scientific computing, algorithms
• Applied topics: modelling, simulation, probability and statistics
• Supporting coursework: programming, data structures, elective courses across computer science and related sciences
• Capstone or research project and opportunities for internships in the Washington, D.C. metropolitan area

Entry requirements

Applicants should hold a recognised secondary school diploma with strong preparation in mathematics. Typical preparation includes pre-calculus and preferably calculus; successful applicants will demonstrate competence in algebra, geometry and problem solving. Some familiarity with programming or computer science is beneficial but not always required.

Marymount evaluates applicants holistically, considering academic records, letters of recommendation, and a personal statement. International applicants must show equivalency of secondary credentials and meet the university's English language proficiency requirements; commonly accepted evidence includes scores from approved English tests or other demonstrated English-language competence.

Career prospects

Graduates with a computational mathematics degree are well placed for roles that require quantitative analysis and computational skills. Common career paths include data analyst, quantitative analyst, software developer, operations research analyst, and roles in finance, engineering, government and technology firms. The degree also provides strong preparation for graduate study in mathematics, computer science, data science or related fields and for professional certification routes (for example actuarial exams or specialised technical certifications).

Marymount's location and industry connections support internship opportunities and networking in the federal, defence, finance and technology sectors, which many students use to transition into entry-level positions or to build experience for graduate programmes.

Why study at Marymount University

Marymount is known for its undergraduate focus and small class sizes that enable close interaction with faculty and personalised mentoring. Students in the computational mathematics concentration benefit from hands-on experiences in computing labs, faculty-led research projects and internship placements facilitated by Marymount's ties to the greater Washington, D.C. region.

The university emphasises experiential learning and interdisciplinary collaboration, allowing mathematics students to take complementary coursework in computer science, physics, economics or business. This combination of rigorous mathematical training, practical computing experience and career-focused support helps graduates move effectively into quantitative roles or further study.