Presbyterian College

What you'll study

This programme blends core mathematical theory with computational methods and numerical modelling. Early semesters focus on foundational topics such as calculus, linear algebra, differential equations and proof-based mathematics. As you progress, you take modules that emphasise computation and applications, including numerical analysis, scientific computing, mathematical modelling, probability and statistics, discrete mathematics and algorithm design.

• Core mathematics: Calculus sequence, Linear Algebra, Ordinary Differential Equations, Real Analysis/Introduction to Proofs.
• Computational and applied topics: Numerical Analysis, Computational Methods, Mathematical Modelling, Applied Linear Algebra, Scientific Programming (often using languages such as Python or MATLAB).
• Statistics and data: Probability, Mathematical Statistics, Data Analysis and Computational Statistics.
• Computer science linkage: Discrete Mathematics, Algorithms, and electives in programming or software development to support computational work.
• Capstone and research: A senior seminar, capstone project or independent research supervised by faculty that emphasises computational modelling, data-driven projects or algorithmic problem solving.
• Electives and general education: Liberal arts courses to broaden communication, critical thinking and domain knowledge; students may choose electives in economics, physics, biology or computer science to deepen applied skills.

Entry requirements

Applicants should hold a high-school diploma (or equivalent) with strong preparation in mathematics. Successful candidates typically have completed courses in pre-calculus and calculus and demonstrate quantitative aptitude. Admissions usually consider the overall academic record, a personal statement, and letters of recommendation. Prior experience with computer programming or exposure to higher-level mathematics is advantageous but not essential; placement testing may determine the appropriate entry-level mathematics course.

Career prospects

Graduates are well placed for careers that require strong quantitative and computational skills. Common destinations include:

• Data analyst or data scientist roles in sectors such as finance, healthcare, technology and government.
• Software developer, algorithm engineer or computational scientist positions where numeric methods and efficient algorithms are applied.
• Actuarial work, risk analysis and quantitative roles in insurance and finance (often following professional exam preparation).
• Scientific and engineering research roles that require modelling and simulation expertise.
• Graduate study in mathematics, applied mathematics, statistics, computer science or related fields for careers in academia or advanced technical roles.

Why study at Presbyterian College

Presbyterian College offers a small liberal-arts environment with close faculty mentorship, enabling students to undertake substantial independent research and capstone projects in computational mathematics. The department emphasises undergraduate involvement in real-world projects, internships and cross-disciplinary collaboration, providing opportunities to work with faculty on computational modelling and data analysis. Small class sizes foster interactive learning and frequent faculty contact, while campus resources such as computing labs and access to internship networks help students build practical skills sought by employers and graduate programmes.