Fairmont State University

What you'll study

The programme balances core mathematical theory with computational and applied coursework. Early courses build a solid foundation in calculus, linear algebra and discrete mathematics, followed by real analysis and abstract algebra to develop rigorous reasoning. Computational and applied modules include numerical analysis, scientific computing, numerical linear algebra, mathematical modelling, optimisation and probability and statistics.

• Introductory and advanced calculus (single and multivariable)
• Linear algebra and matrix theory
• Differential equations and dynamical systems
• Real analysis and proof-based mathematics
• Numerical analysis and computational methods
• Scientific programming (Python, MATLAB or equivalent) and data structures
• Probability, mathematical statistics and stochastic modelling
• Discrete mathematics and combinatorics
• Applied electives such as optimisation, numerical PDEs, machine learning foundations or computational biology
• Capstone project or senior seminar involving a computational modelling or data-analysis project

Students are encouraged to complement the major with minors or courses in computer science, engineering, economics or physics to broaden applied opportunities. Hands-on work in computer labs and opportunities for undergraduate research or internship projects are integral to the curriculum.

Entry requirements

Applicants should have a high-school diploma or equivalent with a solid background in mathematics. Typical preparation includes algebra, geometry, precalculus and preferably calculus. Admission considers overall academic record, letters of recommendation and a personal statement; standardised tests may be optional or considered where submitted.

For transfer students, college-level coursework in calculus and college algebra or their equivalents are normally required. International applicants must meet Fairmont State University’s general admissions and English-proficiency requirements.

Career prospects

Graduates with a computational mathematics specialism are well positioned for roles that require quantitative modelling and computational skills. Common entry careers include:

• Data analyst or data scientist in finance, healthcare, government and technology
• Software developer or engineer focused on numerical methods and scientific computing
• Quantitative analyst, modelling specialist or operations research analyst
• Actuarial analyst (with additional exam preparation)
• Technical roles in engineering firms, energy companies and research labs
• Graduate study in applied mathematics, computer science, statistics, engineering or related fields
• Secondary mathematics teaching with appropriate certification pathways

Practical project experience, programming competence and internship placements substantially improve employability. The programme also provides a strong foundation for graduate-level research or professional qualifications.

Why study at Fairmont State University

Fairmont State offers small class sizes and accessible faculty whose teaching emphasises mentorship and applied problem solving. The university maintains computer and STEM labs equipped for numerical computing and modelling, supporting student projects and capstones.

Students benefit from regional industry links and internship opportunities that connect classroom learning to workplace experience. Fairmont State also supports undergraduate research and provides pathways to graduate study and teacher certification. The campus environment is suited to students who prefer hands-on, supportive undergraduate learning in a smaller public university setting.