Middle Tennessee State University (MTSU)

What you'll study

The programme blends foundational mathematics and computing with applied data analysis. Core topics typically include calculus and linear algebra, probability and mathematical statistics, data structures and algorithms, databases and SQL, and introductory and advanced programming (commonly Python and/or R). Applied and specialised modules commonly cover machine learning, data mining, data visualisation, big data technologies, optimisation, and computational modelling.

Practical work is emphasised through laboratory courses, project-based modules and a senior capstone or practicum in which students apply pipelines from data acquisition and cleaning through modelling, evaluation and presentation. Students also take coursework in data ethics, reproducible research and domain electives that allow application of data science methods to areas such as business, health, engineering or the social sciences.

The degree structure typically comprises a balance of general education requirements, core data science courses, supporting mathematics and computing classes, and open electives or concentrations. Options for internships, undergraduate research with faculty, and collaborative team projects support hands-on experience and professional readiness.

Entry requirements

Admission to MTSU’s bachelor programmes normally requires a high school diploma or equivalent. Successful applicants usually present a strong background in mathematics (algebra, precalculus or calculus) and evidence of analytical aptitude. Prior exposure to programming is beneficial but not always mandatory; introductory programming courses can be completed during the first year if needed.

Typical materials for application include high school transcripts and any college transfer transcripts. Transfer applicants will be evaluated on completed college coursework and grades. Standardised tests (SAT/ACT) may be considered according to institutional policies; applicants should consult MTSU admissions for current requirements. International applicants must meet English language proficiency standards and provide comparable academic records.

Career prospects

Graduates of a data science bachelor’s programme are prepared for a wide range of roles in industry, government and research. Common entry-level positions include:

• Data analyst – preparing and interpreting datasets to support business decisions
• Data scientist – developing predictive models and applying machine learning techniques
• Data engineer – building and maintaining data pipelines and infrastructure
• Business intelligence analyst – designing dashboards and translating analytics for stakeholders
• Machine learning engineer – implementing models for production systems

Alumni also move into specialised roles in sectors such as healthcare analytics, finance, marketing analytics, manufacturing, logistics and public policy. The degree also provides a solid foundation for graduate study in data science, computer science, statistics or related disciplines.

Why study at Middle Tennessee State University (MTSU)

MTSU offers a student-centred learning environment with accessible faculty and opportunities for applied experience. The university’s emphasis on hands-on labs, internship connections with regional employers and options for undergraduate research help students build practical portfolios and professional networks. Cross-disciplinary collaboration with departments such as computer science, mathematics and business enables students to tailor their studies to specific industries or research interests.

MTSU’s campus resources—computer labs, research centres and career services—support skill development, practicum placements and job search activities. For students seeking a practical, interdisciplinary pathway into data-driven careers or graduate programmes, MTSU provides structured coursework combined with experiential learning opportunities to transition from classroom concepts to real-world projects.