Kettering University

What you'll study

The Applied Mathematics curriculum blends core mathematical theory with computational and applied methods used in industry and research. Students take a sequence of foundational courses in calculus, linear algebra and differential equations before moving to intermediate and advanced topics that emphasise modelling and computation.

• Foundations: Single- and multivariable calculus, linear algebra, introductory proof-based mathematics and differential equations.
• Core applied topics: Numerical analysis and scientific computing, mathematical modelling, optimisation and operations research, probability and mathematical statistics.
• Computation and data: Programming for mathematicians (commonly using languages such as Python or MATLAB), data analysis, numerical linear algebra and algorithms for large-scale computation.
• Advanced electives: Partial differential equations, stochastic processes, time series analysis, computational fluid dynamics, discrete mathematics and combinatorics, and topics in machine learning or data science.
• Applied experience: A capstone or senior project that requires modelling, simulation, or data-driven analysis of a realistic engineering, business or scientific problem; opportunities for joint projects with engineering and computer science students.
• Co-op and experiential learning: Integration with Kettering’s cooperative education model, enabling students to alternate academic study with paid work placements in industry to apply mathematical tools to practical problems.

Entry requirements

Admission to the programme normally requires a high school diploma or equivalent with strong preparation in mathematics. Typical applicants present coursework in precalculus and calculus where available, and good grades in science and mathematics. Admissions will consider your overall academic record, recommendation(s), and an application personal statement describing your interest in mathematics and applied problem-solving.

Applicants who have completed college-level mathematics or AP/IB credits may receive advanced placement into the calculus sequence. International applicants must demonstrate English language proficiency through recognised tests or by meeting the university’s alternative pathways.

Career prospects

Graduates with a degree in Applied Mathematics are prepared for quantitative roles across industry, government and research. The programme’s emphasis on computation and modelling equips students for technical careers where mathematical analysis drives decision-making.

• Data analyst, data scientist or business analyst roles, applying statistical and computational methods to extract insight from data.
• Quantitative analyst or model developer in finance, insurance or risk management, using probability, stochastic modelling and optimisation techniques.
• Operations research analyst or optimisation specialist in manufacturing, logistics and supply chain, developing efficient systems and decision-support tools.
• Software engineering or computational scientist positions that require strong numerical and algorithmic skills.
• Further study in mathematics, applied mathematics, statistics, engineering or computer science, including graduate school or professional certification (for example, actuarial exams for those pursuing actuarial careers).

Why study at Kettering University

Kettering’s curriculum is industry-oriented and closely integrated with cooperative education, giving applied mathematics students substantial hands-on experience solving real problems for employers. The university’s strong ties to automotive, manufacturing and technology sectors provide internship and co-op placements where mathematical modelling and data analysis are directly applied.

Students benefit from small class sizes and close interaction with faculty who have applied and interdisciplinary research interests. The combination of classroom instruction, computing resources, project-based learning and co-op placements helps graduates move quickly into technical roles or competitive graduate programmes.