University of Technology Sydney

What you'll study

The program combines core technical subjects, applied analytics practice and business-focused units to prepare you to turn data into decision-ready insights. Learning is practice-oriented and emphasises working with real datasets and industry problems.

• Core analytics foundations – probability and statistics for analytics, predictive modelling and machine learning fundamentals.
• Data engineering and management – data wrangling, databases, data architecture and working with structured and unstructured data.
• Advanced analytics techniques – optimisation, time series analysis, natural language processing and deep learning techniques as applied to business problems.
• Data visualisation and communication – storytelling with data, dashboarding and communicating insights to non-technical stakeholders.
• Business and ethics – analytics strategy, value realisation, privacy, governance and ethical use of data.
• Capstone industry project – an applied project with an industry partner or simulated business case that integrates technical and commercial skills.
• Electives and specialisations – options typically allow deeper study in areas such as marketing analytics, finance analytics, operations and supply chain analytics, or AI applications.

Entry requirements

Applicants are normally required to hold a recognised bachelor’s degree. While graduates from quantitative disciplines are well placed for the program, applicants from other backgrounds with relevant work experience or demonstrated quantitative competence are also considered.

• Academic transcripts and a degree qualification from a recognised institution.
• Evidence of quantitative ability — this may be demonstrated through prior study in mathematics, statistics, computing or related subjects, or through professional experience; some applicants may be required to complete bridging coursework.
• Professional résumé and a personal statement outlining reasons for applying and relevant experience.
• English language proficiency evidence if your previous study was not in English (accepted tests include IELTS, TOEFL and others recognised by the university).
• Additional documentation such as references, a portfolio of work or an interview may be requested for borderline or professional-entry applicants.

Career prospects

Graduates move into a wide range of analytics and data-focused roles across sectors including finance, consulting, retail, technology, government and healthcare. Typical career paths include:

• Data Analyst / Business Analyst
• Data Scientist or Machine Learning Engineer
• Analytics Consultant or Insights Manager
• Business Intelligence Developer or Data Engineer
• Roles in analytics strategy, product analytics and operations analytics

The program’s applied capstone and industry links are designed to help build workplace-ready skills and professional networks that support job transition and career development.

Why study at University of Technology Sydney

UTS emphasises industry-relevant education with an applied approach to business analytics. The university’s strong connections with Sydney’s business and technology sectors provide access to industry projects, guest practitioners and potential employers.

• Practical learning: coursework and capstone projects focus on real-world datasets and business problems.
• Industry engagement: collaborations with companies and industry partners help students develop employable skills and professional networks.
• Location and facilities: based in Sydney, the program benefits from proximity to a diverse corporate and tech ecosystem and contemporary analytics teaching facilities and labs.
• Interdisciplinary environment: the course combines technical, analytical and business disciplines to prepare graduates to communicate and implement analytics solutions within organisations.