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Bachelor of Mathematics (Data Science)
Bachelor of Mathematics (Data Science)

Bachelor of Mathematics (Data Science)

  • ID:UOSA610128
  • Level:3-Year Bachelor's Degree
  • Duration:
  • Intake:
  • Type:Full-time

Fees (AUD)

  • Application Fee:$200.00
  • TuitionFee/Year:$33,600.00
  • LivingFee/Year:$18,000.00
  • InsuranceFee/Year:$530.00
  • Application Fee:$200.00
  • TuitionFee/Year:$33,600.00
  • LivingFee/Year:$18,000.00
  • InsuranceFee/Year:$530.00
Estimated Total/program:
Accept letter

Admission Requirements

Entry requirements

The admission criteria have been grouped to assist you to easily find the information most relevant to your circumstances. However, you may fit into more than one and the university will consider applicants against each of the relevant criteria.

Applicants are required to meet one of the following criteria with a competitive result, and demonstrate that they fulfil any prerequisite requirements and essential requirements for admission:

  • Recent secondary education
    • Meet any prerequisite requirements with a minimum grade of C- or equivalent


  • Qualify for the South Australian Certificate of Education (SACE), and achieved a competitive Selection Rank (ATAR), or
  • Complete secondary qualifications equivalent to SACE, or
  • Complete the International Baccalaureate Diploma with a minimum score of 24 points

Applicants who have not achieved the Selection Rank required for automatic selection may be selected for any remaining places based on the grades of their year 12 subjects.


  • Higher education study
    • Complete or partly complete a recognised higher education program at a recognised higher education institution, or
    • Complete at least four Open Universities Australia (OUA) courses at undergraduate level or above


  • Vocational Education and Training (VET)
    • Complete an award from a registered training organisation at Certificate IV or above


  • Work and life experience
    • Qualify for Special Entry, or
    • Complete a UniSA Foundation Studies program or equivalent, or
    • Hold completed secondary qualifications equivalent to SACE obtained more than 2 years in the past

English requirements

  • IELTS total 6.0

Course Information

Data scientists are in increasing demand globally1. More and more organisations seek to analyse and interpret vast amounts of data and make sure it is used in intelligent, valuable ways.

This degree is designed to produce job-ready graduates to meet this industry need, and to fill the growing range of work opportunities in the market. Successful maths and data scientists draw on skills from a range of complementary disciplines, so this degree offers a balanced mix of mathematics, information technology and data science. In your final year you’ll complete an industry-based project to experience real-world challenges and gain workplace experience.

You will graduate ready to work in a data science role in industry or the public sector. Because data science is also a tool that supports research across an increasing range of disciplines, you could also choose to continue with a Bachelor of Applied Science (Honours) (Industrial and Applied Mathematics), a Bachelor of Information Technology (Honours), a Master of Data Science or eventually a PhD.

Flexible study opportunities are available, you can study full-time or part-time

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Pre Courses

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Career Opportunity

Career Opportunity

The field of data science field is evolving at a rapid rate. It will continue to grow as savvy business leaders integrate analytics into every facet of their organisations. Analytics, maths, science, data, and reasoning are becoming embedded into decision-making processes, every day and everywhere in the business world1.

Careers to consider:

  • big data visualiser: using visualisation software to analyse data, drawing implications and communicating findings; providing input on database requirements for reporting/analytics; acquiring, managing and documenting data (e.g. geo-spatial); creating visualisations from data or GIS data analysis
  • data scientist: understanding interfaces, data migrations, big data and databases; taking the lead in processing raw data and determining the best types of analysis; mining large volumes of data to understand user behaviours and interactions; communicating data findings to IT leadership and business leaders to promote innovation
  • big data researcher: extracting data from relational databases; manipulating and exploring data using quantitative, statistical and visualisation tools; selecting appropriate modelling techniques so predictive models are developed using rigorous statistical processes; maintaining effective processes for validating and updating predictive models
  • data miner: collecting data from numerous databases; helping businesses to make decisions about how data should be analysed in areas such as expenses, profitability, and for other important business decisions

Ability to settle

Overseas Student Health Cover

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