University of Vermont

What you'll study

The Applied Computer Science track emphasises practical problem solving and software engineering while covering the theoretical foundations of computing. The curriculum typically combines core computer science courses, mathematics requirements, laboratory work, and applied electives.

• Core computing subjects: introductory and intermediate programming, data structures and algorithms, computer organisation and architecture, operating systems, and discrete mathematics.
• Applied and systems topics: software engineering and project-based development, databases, networks and distributed systems, cybersecurity fundamentals, and embedded systems.
• Specialist and elective modules: courses in machine learning and artificial intelligence, human–computer interaction, graphics and visualization, mobile and web development, parallel and high-performance computing, and data science.
• Mathematics and supporting courses: calculus, linear algebra, probability and statistics to support computing and data-oriented work.
• Practical experience: supervised lab classes, individual and group projects, a capstone or senior design project, and opportunities for internships or cooperative placements.
• Research and independent study: options to undertake undergraduate research with faculty in areas such as artificial intelligence, systems, networking, software engineering and computational science.

Entry requirements

Admission to the Bachelor of Science in Computer Science typically requires a secondary-school qualification equivalent to a US high school diploma. Strong achievement in mathematics is expected; prior experience in programming is advantageous but not always mandatory.

• Academic preparation: evidence of strong performance in mathematics (algebra, precalculus or calculus) and science courses.
• Recommended background: prior coursework or extracurricular experience in programming (languages such as Python, Java or C++) or computer science principles helps candidates prepare for first-year work.
• Application components: academic transcripts, a personal statement that explains interest in computing and career goals, and letters of recommendation as required by the university's undergraduate admissions process.
• Standardised tests: the university has flexible policies regarding standardised tests; applicants should consult the admissions office for current guidance.
• Transfers and advanced standing: students with prior college coursework may be eligible for transfer credit subject to departmental review, and placement exams can determine appropriate starting courses.

Career prospects

Graduates with a BS in Applied Computer Science are prepared for a broad range of technical roles in industry, government and research, or for further graduate study. The programme’s practical emphasis helps students transition quickly into professional environments.

• Typical entry-level roles: software developer/engineer, web or mobile application developer, systems engineer, database administrator, and quality assurance/test engineer.
• Data and analytics roles: data analyst, junior data scientist or business intelligence developer for graduates who take data science and statistics electives.
• Security and systems roles: cybersecurity analyst, network engineer or embedded systems developer for those who specialise in systems and security.
• Further study and research: many graduates pursue graduate degrees (master’s or PhD) in computer science, data science or related fields.
• Entrepreneurship and interdisciplinary careers: the programme also supports graduates who join startups, found companies, or work at the intersection of computing with fields such as health, environmental modelling, and the arts.

Why study at University of Vermont

The University of Vermont combines a research-active computer science department with a supportive undergraduate environment. Students benefit from hands-on learning, small class sizes in upper-level modules, and close access to faculty for mentorship and research collaboration.

• Applied learning: emphasis on lab work, team software projects and capstone experiences that mirror industry practice.
• Research opportunities: undergraduates can join faculty-led research in areas such as machine learning, systems, cybersecurity and computational modelling.
• Location and industry links: Burlington’s tech ecosystem and regional industry partnerships provide practical internship and employment opportunities.
• Student community and support: active computing student organisations, hackathons, tutoring and career services to help students develop technical skills and prepare for job searches or graduate study.
• Interdisciplinary options: easy collaboration with other colleges within the university—such as mathematics, engineering, business and the natural sciences—enabling customised study paths that integrate computing with other domains.