Loyola University Chicago

What you'll study

This programme integrates core computer science topics with the mathematical foundations that underpin them. You will study programming fundamentals and software development, data structures and algorithms, computer systems and architecture, operating systems, and databases. Mathematical coursework typically includes calculus, linear algebra, discrete mathematics, probability and statistics, and courses in mathematical reasoning and analysis.

Throughout the degree you will encounter hands‑on laboratory work, programming projects and collaborative assignments. Advanced and elective options commonly available allow you to explore artificial intelligence and machine learning, numerical analysis, computational modelling, cryptography and cybersecurity, computer graphics, networks, and optimisation. The curriculum is designed to culminate in a senior capstone or independent research project where students apply mathematics and computer science methods to a substantive problem.

Typical modules and subjects

• Introduction to Programming (Python, Java or C++)
• Data Structures and Algorithms
• Discrete Mathematics
• Calculus I–III
• Linear Algebra
• Probability and Statistics for Computing
• Computer Organization and Operating Systems
• Databases and Software Engineering
• Numerical Methods / Scientific Computing
• Electives: Machine Learning, Cryptography, Computer Networks, Computer Graphics

Entry requirements

Applicants should hold a secondary school diploma or equivalent with a strong preparation in mathematics. Successful candidates typically demonstrate achievement in higher‑level mathematics courses (for example, calculus) and perform well in science and problem‑solving subjects. Prior programming experience is helpful but not always required; evidence of analytical ability through coursework, projects or competitions will strengthen an application.

Loyola looks for a strong overall academic record and engagement beyond grades — such as computer science clubs, math competitions, research projects or internships. Applicants may also be asked to provide a personal statement and academic references. Prospective students unsure about specific requirements should consult the university’s admissions office for guidance on qualifications and pathways into the programme.

Career prospects

Graduates are prepared for a wide range of careers that draw on both mathematical reasoning and computing skills. Common roles include software developer/engineer, data scientist or analyst, quantitative analyst, systems architect, cybersecurity specialist, and roles in machine learning or AI engineering. The combination of rigorous maths and practical computing also prepares students for graduate study in computer science, applied mathematics, statistics, or related fields.

Many students secure internships and first roles in Chicago’s technology and finance sectors, in consulting firms, or with startups and research organisations. The programme’s emphasis on project work, teamwork and communication helps graduates transition to professional environments and pursue licensure or advanced qualifications where relevant.

Why study at Loyola University Chicago

Loyola University Chicago offers a student‑centred learning environment grounded in the Jesuit tradition of intellectual inquiry and service. The university’s location in a major metropolitan area provides access to internships, industry partners and research collaborations across technology, finance, healthcare and government.

Students benefit from small class sizes in upper‑level courses, opportunities to work closely with faculty on research and capstone projects, and access to career services that support internship and job placement. The programme encourages interdisciplinary engagement, allowing students to combine computing and mathematics with fields such as economics, physics, biology or business depending on their interests.

Overall, Loyola’s programme is designed to develop both theoretical depth and practical skills, producing graduates who are well prepared for technical careers or further study.