Colorado State University

What you'll study

The programme blends foundations in mathematics and statistics with computer science and applied data techniques. Core topics typically include:

• Programming and software development (Python and/or R, data structures, algorithms, software engineering practices for reproducible analysis)
• Mathematics for data science (calculus, linear algebra, discrete mathematics and numerical methods)
• Statistical methods (probability theory, inferential statistics, regression, experimental design)
• Machine learning and predictive modelling (supervised and unsupervised learning, model evaluation and selection)
• Data management and engineering (relational and non‑relational databases, data cleaning, pipelines, basics of big data technologies)
• Data visualisation and communication (exploratory graphics, dashboards, communicating results to non‑technical audiences)
• Ethics, privacy and policy (responsible data use, algorithmic fairness and legal/social implications of data-driven systems)
• Applied electives and domain coursework allowing students to tailor study to areas such as environmental science, business analytics, bioinformatics or engineering

The degree normally culminates in a capstone project or practicum in which students work on a real dataset or partner with industry, government or campus research groups to apply methods from the curriculum. Students have opportunities for undergraduate research and internships that complement classroom learning.

Entry requirements

Applicants are expected to hold a high school diploma or equivalent with strong achievement in mathematics. Recommended preparation includes coursework in:

• Algebra, precalculus and calculus
• Computer science or programming (where available)
• Statistics or data‑related courses if offered

Admission to Colorado State University and to the data science major typically considers academic record, strength of quantitative background and overall fit. Applicants for whom English is not a first language must meet the university's English proficiency requirements. Transfer applicants should provide college transcripts; prior coursework in calculus, introductory programming and basic statistics will strengthen an application.

Career prospects

Graduates are prepared for a wide range of roles that require quantitative and computational skills. Common career paths include:

• Data scientist or data analyst, developing models and extracting insights from data
• Machine learning engineer, implementing scalable predictive systems
• Data engineer, building and maintaining data pipelines and storage solutions
• Business analyst or consultant, translating data findings into business decisions
• Research assistant or further study in graduate programmes in data science, statistics, computer science or related fields

Graduates find employment across technology, finance, healthcare, government, agriculture and environmental organisations—particularly within Colorado's active tech and start‑up community as well as national and international firms that recruit graduates with strong quantitative skills.

Why study at Colorado State University

Colorado State University is a research‑intensive, land‑grant institution with an emphasis on applied science and cross‑disciplinary collaboration. The data science programme draws on faculty expertise across statistics, computer science and domain departments, enabling students to combine rigorous methodological training with applied projects. Students benefit from access to research computing resources, internship and industry partnership opportunities in the Fort Collins and Denver‑area tech ecosystems, and campus support services such as career services and undergraduate research programmes. The curriculum emphasises experiential learning, preparing graduates to move directly into technical roles or to continue into specialised graduate study.