Southern Methodist University

What you'll study

This programme combines core computer science theory with applied, project-based coursework. Students study advanced topics such as algorithms and data structures, operating systems, and software engineering, and choose elective streams to specialise in areas like machine learning and artificial intelligence, data science, cybersecurity, cloud and distributed systems, human–computer interaction, or robotics.

• Core modules typically include advanced algorithms, computer systems/operating systems, software design and engineering practices, and database systems.
• Applied and elective modules often cover machine learning, deep learning, data mining, big data platforms, network and cloud computing, secure systems, embedded systems, and HCI.
• Capstone / practicum is a substantial applied project or practicum with industry or faculty supervision, allowing students to integrate coursework into a real-world system or research prototype.
• Research option may be available for students who wish to pursue a thesis under the supervision of Lyle School faculty, preparing for doctoral study or research-focused careers.
• Delivery formats can include day and evening classes and may provide flexibility for part-time study; coursework emphasises coding, system design, performance evaluation and team-based development.

Entry requirements

Applicants are expected to hold a recognised bachelor’s degree. Candidates with a degree in computer science, engineering, mathematics or a related quantitative discipline are typically competitive. Applicants from other backgrounds may be considered if they demonstrate sufficient programming and mathematics preparation.

• Transcripts showing undergraduate study in relevant subjects; a strong record in programming, data structures and discrete mathematics is desirable.
• Statement of purpose describing academic and professional goals and reasons for selecting the applied track.
• Letters of recommendation (usually two or three) from academic or professional referees who can speak to technical ability and readiness for graduate study.
• Curriculum vitae or résumé detailing relevant work experience, projects and technical skills.
• Proof of English language proficiency for international applicants (where applicable).
• Standardised test requirements (such as the GRE) may be considered optional or required depending on applicant background; consult the programme for current policy.

Career prospects

Graduates are prepared for technical and engineering roles across the technology sector and in organisations that rely on software and data-driven systems. The applied emphasis equips students to move directly into development and operational roles as well as technical leadership positions.

• Software engineer / developer — designing, implementing and maintaining software systems.
• Machine learning engineer or data scientist — building models, pipelines and production data products.
• Systems architect or cloud engineer — planning and deploying scalable distributed systems and cloud services.
• Cybersecurity analyst or engineer — securing systems, performing assessments and building defensive solutions.
• Embedded systems or robotics engineer — developing firmware and integrated systems for hardware platforms.
• Technical product manager or engineering lead — combining technical expertise with product and team leadership.
• Further study — students aiming for research or academic careers may transition to doctoral programmes.

Why study at Southern Methodist University

Southern Methodist University’s computer science programmes are housed in the Lyle School of Engineering, located in the Dallas–Fort Worth metroplex — a major regional technology and business hub. The university emphasises close faculty-student interaction, applied projects with industry partners, and opportunities to collaborate across disciplines such as business and data analytics.

• Strong industry connections and internship opportunities in a large, diverse regional tech ecosystem.
• Access to research labs and faculty whose interests span software engineering, AI, security, data science and systems.
• A programme structure that supports both full-time and part-time students, with practicum and capstone options that build practical, portfolio-ready experience.
• Career services, employer events and an active alumni network that help graduates move into technical and leadership roles.