Ripon College

What you'll study

This programme builds a strong foundation in pure and applied mathematics while emphasising computational methods, numerical analysis and scientific programming. In the early years you will study calculus, linear algebra, discrete mathematics and probability and statistics to establish the core mathematical toolkit. As you progress, typical modules include numerical analysis, differential equations, real analysis, algorithm design and analysis, computational modelling, scientific computing (with languages such as Python and MATLAB), data structures, and introductory machine learning.

The course structure balances lecture courses, problem classes and lab‑based units. Students take advanced electives such as computational linear algebra, optimization, stochastic modelling, and high‑performance computing. There is a strong emphasis on project work: students normally complete a capstone project or honours thesis involving original computational work—often in collaboration with faculty across disciplines such as physics, economics or biology. Opportunities for summer research, internships and independent study are integrated into the programme.

Typical modules and activities

• Calculus I–III and Multivariable Calculus
• Linear Algebra and Matrix Computations
• Introduction to Proofs / Real Analysis
• Differential Equations and Dynamical Systems
• Numerical Analysis and Scientific Computing
• Algorithms and Data Structures
• Probability, Statistics and Statistical Computing
• Optimization and Computational Modelling
• Capstone Project / Senior Thesis with an applied computational component
• Internships, summer research and cross‑disciplinary projects

Entry requirements

Applicants are expected to demonstrate strong preparation in mathematics. Typical successful candidates have substantial high‑school mathematics (including calculus where available) and experience with problem solving. Ripon College places weight on academic transcripts, recommendation letters, and evidence of quantitative aptitude; applicants with prior programming experience or coursework in computer science are also well suited to the computational stream.

For applicants from different systems, equivalent secondary qualifications with strong performance in mathematics are required. Mature applicants and those with non‑traditional backgrounds are considered; relevant workplace experience, portfolios of projects or prior college coursework in quantitative subjects can support an application. The college also looks for evidence of intellectual curiosity and the ability to work independently, as many projects involve self‑directed computational work.

Career prospects

Graduates with a computational mathematics background from Ripon College are well placed for careers that combine quantitative reasoning and computing. Common paths include data science and analytics, software and algorithm development, quantitative finance and risk analysis, actuarial work, scientific and engineering modelling, and operations research. The programme’s emphasis on coding, numerical methods and project experience also prepares students for graduate study in applied mathematics, statistics, computer science, engineering and related fields.

Because Ripon College emphasises undergraduate research and close faculty mentoring, graduates often move into research assistantships or competitive graduate programmes. Career services and internship networks help students secure placements in technology firms, consulting, research labs and public‑sector organisations.

Why study at Ripon College

Ripon College offers a small liberal‑arts environment with close faculty support, so students in the mathematics programme benefit from small classes, frequent contact with professors and ready access to research opportunities. The college encourages cross‑disciplinary collaboration, allowing computational mathematics students to work with departments such as economics, biology and physics on applied projects.

Students have access to modern computing facilities and software used in industry and research, and the curriculum emphasises hands‑on, project‑based learning. The college’s career and internship services, alumni network and emphasis on undergraduate research make it a strong setting for students who want both a rigorous mathematical education and practical computational experience.