City University of Seattle

What you'll study

The programme blends foundational mathematics and computer science with applied statistics, machine learning and data engineering. Typical areas of study include programming for data science (Python and libraries such as pandas and NumPy), data structures and algorithms, probability and inferential statistics, linear algebra, databases and SQL, data visualisation, machine learning and predictive modelling, and big-data technologies and cloud platforms.

Students normally complete a sequence of core courses that build analytical and computational skills, supported by elective options that allow specialisation in topics such as natural language processing, computer vision, time-series analysis, business analytics, or cloud-based data systems. Practical learning is emphasised through lab work, project-based courses and a capstone or practicum in which students work on an applied data problem, often in partnership with local organisations or online industry partners.

Entry requirements

Applicants are expected to have a high school diploma or equivalent. Typical academic prerequisites include strong performance in mathematics (algebra and pre-calculus or calculus) and evidence of quantitative aptitude. Admissions may consider prior coursework in computer science or experience with programming as an advantage, though introductory programming courses are usually provided for students without previous experience.

For transfer applicants, accepted college-level credits in mathematics, statistics or computing can be applied toward the degree. International applicants must demonstrate English language proficiency through approved tests or equivalent institutional measures. Selection is based on academic records and other supporting materials such as personal statements; some applicants may be advised to take preparatory coursework before starting the degree if they lack key prerequisites.

Career prospects

Graduates are prepared for roles that require combining statistical reasoning with software engineering and data-handling skills. Common entry-level roles include data analyst, junior data scientist, business intelligence analyst, data engineer, and machine learning engineer. With experience, alumni move into senior data scientist, analytics lead, data engineering architect or analytics consultant roles. The programme also provides a foundation for further study at the master’s level in data science, statistics, computer science or related fields.

Because of City University of Seattle’s connections with the Seattle technology and business community and its emphasis on applied projects, graduates often find opportunities in technology companies, finance, healthcare, government agencies, consulting firms and startups where data-driven decision making is central.

Why study at City University of Seattle

City University of Seattle offers flexible delivery formats, including evening and online options, which suit working students and those who need a non-traditional schedule. The university emphasises career-relevant education with small class sizes and faculty who have industry experience in computing and analytics.

Located in a major technology hub, the institution provides access to local industry networks and applied learning opportunities. The programme’s practical focus — hands-on labs, collaborative projects and a culminating capstone — is designed to build a professional portfolio that helps graduates demonstrate skills to employers. City University of Seattle is regionally accredited, and the curriculum is designed to align academic rigour with the technical and communication skills employers expect from data professionals.