University of Tulsa

What you'll study

The programme combines core advanced computing topics with applied electives and a choice of thesis, project or coursework pathways. Core areas typically include advanced algorithms, operating systems, software engineering practices, and principles of computer systems. Students then personalise their course of study through concentrations and electives in subjects such as machine learning and artificial intelligence, data science and big data analytics, cybersecurity, embedded and real‑time systems, and cloud and distributed computing.

• Core modules: advanced algorithms and data structures, operating systems and concurrency, software engineering and design, research methods in computing.
• Applied electives: machine learning and deep learning, database systems and data mining, network security and cryptography, cloud computing and virtualization, embedded systems and IoT, human–computer interaction.
• Project options: a supervised applied project or industrial practicum focused on building a deployable system or conducting an empirical study.
• Research option: a thesis route for students who plan to pursue research careers or PhD study, involving original research under faculty supervision.
• Capstone: non‑thesis students typically complete a capstone project that integrates theory and practice and demonstrates readiness for professional roles.

Entry requirements

Applicants are expected to hold a bachelor’s degree in computer science, computer engineering, or a closely related discipline. Candidates with strong quantitative backgrounds and relevant undergraduate coursework may be considered on an individual basis. Typical application materials include official transcripts, a statement of purpose outlining academic and career objectives, letters of recommendation, and a current CV or resume.

International applicants must demonstrate English language proficiency by providing results from a recognised test when applicable. Prior preparation in programming, discrete mathematics, and core computing subjects is normally required; some applicants without a conventional computing degree may be admitted conditionally and asked to complete prerequisite modules.

Career prospects

Graduates emerge with hands‑on skills suited to immediate employment in software development, data science, systems engineering and cybersecurity roles. Common job titles include software engineer, data scientist/analyst, systems or cloud engineer, cybersecurity analyst, and embedded systems developer. The applied nature of the programme also prepares graduates for roles in technology management, product engineering, and engineering teams within energy, aerospace, telecommunications and finance sectors.

For those interested in research and academia, the thesis pathway provides preparation for PhD programmes and research positions in industry R&D labs. The department’s connections with regional employers and emphasis on project work often support internship and job placement opportunities.

Why study at University of Tulsa

The University of Tulsa provides a small‑community learning environment within a research university, giving students access to attentive faculty supervision and hands‑on research and project opportunities. The Computer Science department collaborates with engineering and science disciplines, enabling interdisciplinary projects relevant to local and national industry needs.

Students benefit from smaller class sizes, opportunities for graduate assistantships, and access to modern computing facilities and labs. The university’s location supports industry engagement and internships with regional technology, energy and aerospace employers, while a focus on applied outcomes helps graduates transition quickly into professional roles or further study.