COURSE CURRICULUM

The Bachelor of Science (B.S.) in Mathematics at the University of New Hampshire is the most intensive and theory-driven undergraduate mathematics program, designed especially for students who plan to pursue graduate study in mathematics or highly analytical careers in research, science, or quantitative industries. The program requires strong academic performance, with all major courses needing a minimum grade of C- and an overall GPA of at least 2.0 in mathematics coursework. It begins with a rigorous foundation in Calculus I and II, Mathematical Applications with MATLAB or equivalent programming courses, Linear Algebra, Differential Equations, Multidimensional Calculus, Mathematical Proof, and Introduction to Statistical Analysis, ensuring students develop both computational skills and formal reasoning abilities. As the program advances, students complete a deeper sequence of upper-level mathematics courses including Abstract Algebra and Abstract Algebra II, One-Dimensional Real Analysis, Topology, and Complex Analysis, which form the core of advanced theoretical mathematics training. The curriculum is further strengthened by required coursework in physics, including General Physics I and II, which supports mathematical understanding through physical applications and reinforces analytical problem-solving skills. In addition to the core sequence, students select a mathematics elective and two additional advanced courses from areas such as geometry, number theory, combinatorics, commutative algebra, algebraic geometry, real analysis II, and differential geometry, allowing for specialization in pure or applied mathematics. The program culminates in a capstone experience through either a senior seminar or senior thesis, where students engage in independent mathematical investigation and demonstrate mastery of advanced concepts. Overall, this B.S. degree provides a highly structured, rigorous, and mathematically deep education, preparing students for graduate-level study in mathematics, physics, engineering, or related disciplines, as well as for careers requiring advanced quantitative reasoning, such as data science, finance, cryptography, and scientific research.