Southeastern Louisiana University

What you'll study

The Computational Mathematics concentration builds core mathematical understanding alongside courses in numerical computation and scientific programming. You will take the standard calculus and core mathematics sequence (calculus I–III, linear algebra, differential equations) and progress to specialised courses such as numerical analysis, numerical linear algebra, scientific computing, mathematical modelling and optimisation. Complementary coursework commonly includes probability and mathematical statistics, discrete mathematics, algorithms, and elective modules in computer science (for example programming, data structures, and database fundamentals).

Typical programme structure includes foundational coursework in the first two years, intermediate proof-based and applied mathematics in the third year, and advanced computational topics and a capstone experience in the final year. The capstone may be a research project, a computational modelling project with a faculty member, or an industry/agency practicum. Students are also encouraged to use computing environments and languages commonly used in scientific computing (such as Python, MATLAB, R or C/C++) and to gain experience with version control and numerical libraries.

• Calculus I, II, III
• Linear Algebra
• Differential Equations
• Discrete Mathematics
• Probability and Mathematical Statistics
• Numerical Analysis and Numerical Linear Algebra
• Scientific Computing / Computational Methods
• Mathematical Modelling and Optimisation
• Algorithms or Data Structures (computer science elective)
• Senior Capstone or Research Project

Skills developed

Graduates develop mathematical reasoning and proof skills, numerical modelling and algorithmic design, competence in scientific programming, data analysis, and the ability to translate applied problems into computational solutions.

Entry requirements

Entry to the Bachelor of Science in Mathematics with a Computational Mathematics emphasis typically requires a high school diploma or equivalent with a strong background in mathematics. Successful applicants usually have completed pre-calculus or calculus in high school, and are expected to demonstrate proficiency in algebra and problem solving. Typical admissions criteria include a satisfactory high school GPA and submission of standard application materials; standardized test submission policies may vary, so applicants should check current university guidance. Placement testing may be used to determine initial course placement in the calculus sequence.

Transfer applicants should present college-level mathematics coursework for transfer credit consideration. Students without a programming background are still welcome but should be prepared to take introductory programming modules early in the programme.

Career prospects

Graduates with a computational mathematics degree pursue careers that combine quantitative analysis and computing. Common roles include data analyst, quantitative analyst, software developer, computational scientist, operations research analyst, and roles in modelling and simulation. The programme also prepares students for actuarial studies (with additional exam preparation), graduate study in mathematics, statistics, computer science or engineering, and secondary school mathematics teaching (with additional certification requirements).

Because of the practical computing emphasis, alumni can work across industries such as finance, insurance, engineering services, energy, government research labs, manufacturing, healthcare analytics and technology startups. Internship and capstone project experiences help students build a portfolio of applied work for employers or graduate admissions.

Why study at Southeastern Louisiana University

Southeastern Louisiana University offers a personalised learning environment with relatively small class sizes and accessible faculty in the Department of Mathematics and Computer Science. The programme emphasises applied learning through laboratory-based computing, research collaborations with faculty, and opportunities for internships with regional employers. Students benefit from academic advising focused on degree planning, undergraduate research support, and pathways to teacher certification or graduate studies.

The university’s location provides connections to regional industries and government agencies for practicum and internship placements, while campus computing resources and modern software support the computational and modelling elements of the programme. Overall, the programme is geared toward students seeking a balance of mathematical theory and hands‑on computational skills that are in demand across many technical careers.