University of Hull

What you'll study

The programme combines taught modules with a substantial independent research or development project. You will build advanced theoretical understanding and practical skills across core areas of modern computer science while choosing optional modules to tailor the course to your interests.

• Core topics typically include:
  • Advanced algorithms and complexity
  • Machine learning and data mining
  • Distributed and cloud computing
  • Security, privacy and dependable systems
  • Research methods and project planning
• Example optional topics:
  • Natural language processing or computer vision
  • High-performance and parallel computing
  • Advanced software engineering and DevOps
  • Internet of Things and embedded systems
• MSc project: A major independent project (research- or industry-focused) that brings together theory and practical development, typically completed under the supervision of a faculty member and producing a dissertation and artefact or prototype.

Teaching methods include lectures, seminars, laboratory sessions and supervised research. Assessment is normally by a mixture of coursework, practical assignments, exams and the final project.

Entry requirements

Entry is intended for applicants who have a recognised undergraduate degree in computer science, software engineering, or a closely related numerate discipline. Typical requirements are:

• An undergraduate degree at or above the level specified by the university (for example a second-class honours or equivalent); specific offers vary by applicant background.
• Applicants with a lower-class degree but with relevant professional experience, industry certifications or strong evidence of programming and technical ability may be considered.
• Evidence of competence in programming, mathematics and basic algorithmic concepts is normally expected.
• International applicants whose first language is not English must provide proof of English proficiency to meet the university's standard for postgraduate study.

All applicants are assessed on the strength of their academic record, references and personal statement. Some applicants may be invited to interview or asked to provide a short portfolio of relevant work.

Career prospects

Graduates leave prepared for a wide range of technical roles and research pathways. The course emphasises practical skills, applied research and independent project delivery that employers value.

• Technical careers: software engineer, backend/frontend developer, systems architect, cloud engineer
• Data and AI roles: data scientist, machine learning engineer, data engineer
• Security and infrastructure: cybersecurity analyst, network engineer, DevOps engineer
• Research and development: R&D engineer in industry, research assistant, progression to PhD study
• Specialist domains: roles in finance, healthcare informatics, autonomous systems, government and defence where advanced computing skills are required

The department supports employability through project links with industry, careers guidance and opportunities for students to carry out industry-based projects where available.

Why study at University of Hull

The University of Hull offers research-led teaching in computing with active research groups in areas such as machine learning, software engineering, networking and security. You will benefit from small-group supervision for projects, modern computing laboratories and access to software and development tools used in industry.

• Close engagement with academic staff involved in current research ensures course content stays relevant to emerging technologies.
• Opportunities to work on industry-linked projects and to network with regional and national employers through departmental initiatives.
• A supportive postgraduate community and central student services that provide careers advice, skills workshops and guidance on progressing to PhD study or professional roles.

The programme is designed to prepare you for immediate technical impact in industry or a strong foundation for continued academic research.