Michigan Technological University

What you'll study

This interdisciplinary degree blends core mathematics with a broad computer science curriculum. Early years emphasise calculus, linear algebra, discrete mathematics and core programming concepts, while later years move into advanced topics that apply mathematics to computing.

• Core mathematics: calculus sequence, multivariable calculus, linear algebra, ordinary differential equations, real analysis or advanced calculus, probability and mathematical statistics, and numerical analysis.
• Computer science fundamentals: introduction to programming, data structures and algorithms, computer architecture, operating systems, databases, software engineering and programming languages.
• Advanced and applied topics: theory of computation, combinatorics, optimisation, machine learning, numerical methods, scientific computing, cryptography, computer networks and parallel/higher performance computing.
• Capstone and project work: a senior capstone or practicum project that typically involves team-based software development or applied mathematical modelling, often in collaboration with faculty, industry sponsors or research groups.
• Electives and specialisation: students may choose electives to emphasise pure mathematics, computational mathematics, data science, artificial intelligence or systems software. Opportunities exist for undergraduate research and directed study under faculty supervision.

Programme structure

The programme combines lower-division breadth courses with upper-division major requirements and free electives. Students complete a sequence of mathematics and computer science courses alongside general education requirements; many students also undertake internships, co‑ops or research experiences to complement coursework.

Entry requirements

Applicants are expected to have strong preparation in mathematics and science. Typical successful applicants present the following:

• A solid high-school background in mathematics, including algebra, geometry and preferably precalculus or calculus.
• Experience with high-school level programming or demonstrated interest in computing is beneficial (but not always mandatory).
• Competitive overall academic record in secondary school; applicants with advanced coursework (AP, IB, A‑levels or equivalent) in mathematics or computing are well prepared.
• For international applicants, evidence of academic equivalence to U.S. secondary credentials and proficiency in English are required.

Specific admission decisions take into account the full application file, including coursework, recommendations and any relevant extracurricular experience such as coding projects, math competitions or research. Prospective transfer students should consult Michigan Tech's transfer credit policies to determine how previous coursework maps to degree requirements.

Career prospects

Graduates are well positioned for a range of careers that leverage both quantitative reasoning and software skills. Common paths include:

• Software developer, systems engineer, or applications programmer in industry sectors such as software, manufacturing, finance, and technology services.
• Data scientist, machine learning engineer or analytics specialist applying statistical and computational methods to extract insight from data.
• Quantitative analyst or modeller in finance, engineering or energy sectors, using mathematical modelling and numerical methods.
• Roles in cybersecurity, networking and high-performance computing where both theoretical and practical computing skills are valued.
• Graduate study in computer science, applied mathematics, statistics or related fields leading to research, academic or advanced technical careers.

Alumni commonly enter industry through internships, cooperative education experiences and campus career services; many go on to leadership positions in engineering and technology organisations or pursue further study.

Why study at Michigan Technological University

Michigan Tech is a STEM-focused university with an emphasis on hands-on learning, undergraduate research and close faculty mentorship. The Computer Science and Mathematical Sciences departments collaborate to provide interdisciplinary coursework and project opportunities that mirror real-world problems.

• Applied learning: laboratory courses, computing clusters and project-based capstones give practical experience in software development, numerical simulation and data analysis.
• Research and industry links: active research groups in areas such as high-performance computing, machine learning, cybersecurity and applied mathematics offer undergraduate research opportunities and connections to regional and national employers.
• Co‑op and internship support: career services and employer partnerships help students secure experiential learning in industry, government and national laboratories.
• Community and student life: student organisations such as the ACM chapter, Hackathons, and Math Club provide peer learning and extracurricular experience; the campus setting fosters close collaboration between students and faculty.

Together, these strengths make Michigan Tech a strong choice for students who want a rigorous, applied education in mathematics and computer science with ample opportunities for practical experience and career preparation.