University of New Haven

What you'll study

The programme combines core foundations in computing with elective specialisms so you can tailor your study to career goals. Core topics typically include advanced algorithms, software engineering principles, database systems, operating systems and computer networks. Students then choose from electives and advanced options such as machine learning and data mining, big data analytics, cloud computing and distributed systems, cybersecurity and digital forensics, human–computer interaction, mobile and web application development, and IoT systems.

Most students complete a mix of coursework and a culminating practical experience. Options commonly include a team-based capstone project with an industry partner or a research thesis under faculty supervision. Many modules emphasise hands-on labs, contemporary development tools, secure coding practices, and project management. The programme also offers opportunities for applied learning through internships, research projects in computing labs, and collaborative initiatives with local industry partners.

Entry requirements

• Academic background: A recognised bachelor’s degree in computer science, information systems, engineering or a closely related discipline is normally required. Applicants with degrees in other fields may be considered if they demonstrate sufficient quantitative and computing preparation.
• Prerequisites: For applicants without a formal computing degree, prerequisite undergraduate coursework or demonstrated proficiency in programming, data structures, and discrete mathematics may be requested prior to or during early semesters.
• Supporting documents: Official transcripts, a current CV or résumé, a statement of purpose outlining academic and professional objectives, and one or more academic or professional references.
• Standardised tests: The programme may accept or consider standardised test scores where applicable; check the programme admissions guidance for current testing policy.
• English language: International applicants whose first language is not English must demonstrate proficiency through an accepted test or approved institution-level exemption.
• Professional experience: Relevant work experience is advantageous, particularly for applicants seeking part-time study or industry-focused project placements.

Career prospects

Graduates enter a broad range of roles across public and private sectors. Typical job titles include software engineer, systems architect, data scientist or data engineer, cybersecurity analyst, cloud engineer, application developer, IT consultant and systems administrator. The programme’s applied projects and industry links also prepare students for specialist pathways such as digital forensics, network security, machine learning engineering or enterprise systems design.

Alumni progress to positions in technology companies, finance and healthcare organisations, government and defence contractors, start-ups and consulting firms. The degree also provides a strong foundation for further study or research, including progression to doctoral programmes in computing and related disciplines.

Why study at University of New Haven

• Industry-focused curriculum: The University of New Haven emphasises applied learning, with capstone projects, internships and lab-based modules that connect theoretical study to real-world problems.
• Hands-on facilities: Students benefit from computing and cybersecurity laboratories, modern development environments and faculty-led research groups that support applied research and experiential learning.
• Small classes and faculty access: Relatively small class sizes enable direct interaction with faculty who have both academic and industry experience, supporting mentorship and personalised project supervision.
• Career support and local networks: The university’s career services and employer partnerships in the region facilitate internship placements, industry projects and recruitment opportunities across technology sectors.
• Flexible study pathways: The programme commonly supports full- and part-time study, elective specialisations and the option to pursue a capstone or thesis, allowing students to align study with career ambitions.