University of Virginia

What you'll study

This programme combines core computing foundations with elective study in applied information technology topics. Students follow a curriculum that emphasises algorithmic thinking, software engineering, systems design and data-driven methods while choosing specialised modules to align with career goals.

• Core topics: advanced algorithms, operating systems and distributed systems, databases and data management, software engineering and programming languages, and computer architecture.
• Information technology and applied electives: cloud computing and virtualization, networking, cybersecurity and privacy, machine learning and data science, human–computer interaction, big data systems and DevOps practices.
• Project and research work: a capstone project or practicum with industry partners and a thesis option for those who intend to pursue research or a PhD; many students undertake team-based software projects or independent research under faculty supervision.
• Skills developed: system design, scalable data processing, secure application development, advanced programming, empirical evaluation and applied machine learning.

Entry requirements

Admissions seek applicants with a strong undergraduate record in computer science, engineering, mathematics or a closely related discipline. Typical requirements include:

• A bachelor's degree from an accredited institution in computer science, electrical engineering, mathematics or equivalent with substantial computing coursework.
• A competitive academic record demonstrating quantitative aptitude. Specific GPA expectations are set by the programme and may vary.
• Demonstrable programming experience and familiarity with data structures, algorithms and systems; coursework or practical experience in software development is usually expected.
• Supporting documents: academic transcripts, a statement of purpose describing background and objectives, letters of recommendation (usually two or three), and a current CV or résumé.
• International applicants must demonstrate English language proficiency through an approved test unless exempt by institutional policy. Additional materials or credentials may be requested for applicants with non‑standard backgrounds.
• Standardised tests (such as the GRE) may be optional or considered on a case‑by‑case basis depending on the programme's current policy; applicants should check the programme entry requirements before applying.

Career prospects

Graduates enter a broad range of technical roles across industry and government, and many continue into doctoral study. Common career paths include:

• Software engineer or senior developer building scalable applications and services.
• Data scientist or machine learning engineer working on analytical models and data pipelines.
• Systems engineer, site reliability engineer or cloud architect designing and operating distributed systems.
• Cybersecurity analyst, security engineer or privacy specialist protecting systems and data.
• Product engineer, technical consultant or engineering manager in technology companies, startups, finance, healthcare and public sector organisations.
• Research roles in industrial R&D labs or continued academic research towards a PhD.

Why study at University of Virginia

The University of Virginia offers this programme within a research‑active engineering school with faculty expertise across core areas of computing and applied IT. Students benefit from access to interdisciplinary research centres, collaborations with industry partners, and a strong career services network that supports internship and employment opportunities.

• Research strengths: faculty work in artificial intelligence, cybersecurity, networking, data systems and human–computer interaction, enabling students to pursue cutting‑edge projects.
• Industry connections and experiential learning: opportunities for practicum projects, internships and capstones with regional and national technology employers.
• Supportive academic environment: small class sizes in advanced courses, mentorship from faculty, and resources for entrepreneurial or interdisciplinary initiatives involving business, health, and public policy.
• Graduate outcomes: graduates are prepared for technical leadership roles or further study, supported by a professional network and career development services at the university.