North Carolina State University

What you'll study

The programme combines advanced coursework with project or thesis options so you can develop practical skills and research experience. Core topics commonly covered include algorithms and theory, operating systems and distributed systems, software engineering, databases, machine learning and artificial intelligence, computer security and networking. Electives allow further specialisation in areas such as data science, high-performance computing, human–computer interaction, robotics, and applied cryptography.

Students typically follow one of several tracks: coursework-only (professional master’s), a thesis route for those interested in research, or a project-based option that emphasises applied development and industry collaboration. Typical learning activities include graduate seminars, team software projects, research with faculty, and capstone projects that address industry-relevant problems.

Entry requirements

Applicants are expected to hold a bachelor’s degree in computer science, computer engineering or a closely related discipline from an accredited institution. Applicants from other backgrounds with strong quantitative preparation and programming experience may also be considered, but may be asked to complete preparatory undergraduate courses.

• Academic record: a competitive undergraduate GPA (many successful applicants have GPAs around typical graduate admission thresholds).
• Prerequisites: solid foundation in programming, data structures, algorithms, discrete mathematics and calculus; coursework or experience in systems, databases or probability/statistics is advantageous.
• Application materials: official transcripts, a current CV or résumé, a personal statement outlining objectives and relevant experience, and two to three letters of recommendation from academic or professional referees.
• English language proficiency: for applicants whose first language is not English, an approved English proficiency test score is required.
• Standardised tests: GRE scores may be submitted where appropriate; consult the department for current guidance on test requirements.

Career prospects

Graduates move into a wide range of technical and leadership roles across industry and government, including software engineer, systems architect, data scientist, machine learning engineer, security analyst, cloud engineer and DevOps engineer. The applied orientation also prepares students for product-focused roles that bridge engineering and business, such as technical product management or applied research positions in sectors like finance, healthcare, energy and defence.

For those interested in continuing in academia, the thesis option provides preparation for PhD programmes and research careers. The programme’s combination of hands‑on projects and research opportunities makes graduates attractive to startups, large technology firms and research labs.

Why study at North Carolina State University

North Carolina State University’s Department of Computer Science offers a strong mix of applied research and industry engagement. The department hosts active research groups in machine learning, security, networking, software engineering and high-performance computing, and students benefit from access to faculty conducting applied research as well as collaborations with the university’s broader engineering and data science community.

Located within the Research Triangle region, the university has close links with industry partners and research labs, providing opportunities for internships, practicum projects and networking. Students can take advantage of resources such as interdisciplinary centres, well-equipped labs and entrepreneurship support to translate applied research into real-world impact.

Whether you aim to advance technical expertise, transition into a specialised computing role, or prepare for doctoral study, the applied master’s offerings at North Carolina State University provide flexible pathways and practical experience grounded in a research-active environment.