Central Washington University

What you'll study

The programme blends foundational computing and mathematical theory with applied data science techniques. Early coursework typically covers programming in languages such as Python and/or R, discrete mathematics, calculus, linear algebra and introductory statistics. Core data-science modules move on to data structures and algorithms, database systems, statistical inference, exploratory data analysis, and data visualisation.

Advanced and elective courses commonly include machine learning, predictive modelling, natural language processing, big-data technologies, data mining, time-series analysis and optimisation. The curriculum emphasises practical, project-based learning: students analyse real datasets, build end-to-end data pipelines, and produce reproducible analyses. A capstone project or practicum in which students work individually or in teams to solve an applied problem is a typical final-year requirement.

• Introduction to Programming and Software Development
• Calculus and Linear Algebra for Data Science
• Probability and Statistical Inference
• Data Structures and Algorithms
• Databases and Data Management
• Machine Learning and Predictive Analytics
• Data Visualisation and Communication
• Big Data Tools and Cloud-based Workflows
• Capstone Project / Internship / Practicum

Entry requirements

Applicants should hold a high-school diploma or equivalent with a solid background in mathematics. Preparation in algebra, precalculus or calculus and some prior experience with programming will strengthen an application. Central Washington University considers overall academic achievement, required high-school coursework, and supporting materials when assessing applicants.

Transfer students must provide college transcripts; relevant community-college coursework in calculus, statistics, and programming can be applied toward the degree. International applicants should demonstrate proficiency in English. Specific minimum GPAs, prerequisite course lists and documentation requirements are provided by the university and may vary, so consult Central Washington University's admissions pages or an academic advisor for precise guidance.

Career prospects

Graduates are prepared for a range of technical and analytical roles across sectors. Typical entry-level positions include data analyst, business intelligence analyst, machine learning technician, data engineer or software developer with a data focus. With experience, graduates move into roles such as data scientist, machine learning engineer, analytics manager or specialised technical consultant.

Alumni also pursue graduate study in data science, computer science, statistics or related fields. Employers hiring CWU data-science graduates include technology companies, healthcare and biotech firms, financial services, government agencies, and regional businesses requiring data-driven decision making. The programme’s applied projects and internship opportunities help build a portfolio that supports job entry and career progression.

Why study at Central Washington University

Central Washington University offers a focused, undergraduate-centered learning environment with smaller class sizes and direct access to faculty. The data-science degree is designed to be interdisciplinary, enabling students to combine computing and quantitative methods with domain-specific applications. Hands-on laboratories, project-based courses and capstone experiences emphasise practical skills and portfolio development.

The university’s location provides opportunities for internships and collaboration with regional employers and public-sector organisations, while campus computing facilities support work with modern tools and datasets. Academic advising and career services help students plan internships, co-curricular experiences and graduate-school pathways to match their career goals.