University of New Haven

What you'll study

This applied master's emphasises practical problem solving and the application of core computer science principles. Coursework typically covers advanced algorithms, software engineering, databases, computer networks, and systems programming, alongside applied topics such as machine learning, data analytics, cybersecurity, and cloud computing. Students complete a combination of core modules, elective specialisms and a substantial culminating experience — usually a capstone project, practicum with an industry partner, or a research thesis — where they apply methods and tools to a real-world problem.

• Core topics: Advanced Algorithms and Data Structures; Software Engineering and Architecture; Database Systems; Operating Systems and Networks.
• Applied and elective topics: Machine Learning and Data Mining; Big Data Analytics; Applied Artificial Intelligence; Cybersecurity Principles and Practices; Cloud Computing and DevOps; Mobile and Web Application Development.
• Culminating experience: Capstone project or practicum that emphasises design, implementation and evaluation of an applied computing solution; option for a research thesis for students targeting doctoral study.
• Learning format: A mix of lectures, laboratory work, team-based projects and industry-aligned assignments designed to build practical, immediately usable skills.

Entry requirements

Applicants are normally expected to hold a recognised bachelor's degree in computer science, software engineering, information technology or a closely related discipline. Candidates with degrees in other quantitative or engineering fields may be considered but could be required to complete prerequisite undergraduate computing courses to address gaps.

• Academic transcripts: Official transcripts demonstrating prior academic preparation in relevant subjects.
• Supporting documents: A personal statement outlining objectives and relevant experience; curriculum vitae/resumé; letters of recommendation may be requested for some applications.
• Standardised tests and English language: Standardised test requirements vary; applicants should check the programme guidance. International applicants whose first language is not English must demonstrate proficiency through recognised English language tests or approved alternatives.
• Professional experience: Relevant industry experience can strengthen an application, particularly for applicants without a computing undergraduate degree.

Career prospects

Graduates leave equipped for technical and development roles across sectors that rely on software and data-driven solutions. Typical job titles include software engineer, systems developer, data analyst or data scientist, machine learning engineer, cybersecurity analyst, cloud engineer and systems architect. The programme’s applied focus and capstone/practicum options also prepare students for roles that require immediate practical impact, such as technical lead or solutions engineer, and provide a pathway to doctoral study for those interested in research careers.

Why study at University of New Haven

The University of New Haven combines applied teaching with hands-on laboratory facilities and industry engagement. The programme is taught by faculty with both academic and professional experience, and emphasises project-based learning, access to current development and analytics toolchains, and opportunities for internship or practicum placement with regional and national employers. Small class sizes support closer mentorship, and campus career services provide help with internship placement, résumé development and employer connections to support transition into industry or further study.