Bachelor of Mathematics (Data Science)

Maths degrees at UniSA share a common first year. Therefore at the end of first year, you can change to the Industrial and Applied Mathematics specialisation if you wish, and retain credits for the courses you've already done.

If you wish to taken on additional studies after graduation, UniSA offers a Master in Data Science which provides graduates with the analytical and technical skills to effectively extract useful information from Big Data to support the management and operations of an organisation.

Our world-class facilities at Mawson Lakes campus offer an inspiring learning environment such as the multi-million dollar Materials and Minerals Science Learning and Research Hub.

Our degrees emphasise the development of critical thinking, creativity and hands-on learning to produce graduates who are in high demand.

In first year you'll study core subjects in maths and IT. You will focus on building your mathematical and programming skills with courses that include calculus, statistical methods, fundamentals of programming, and databases.

You will then move into your applied data science studies. You'll study cross-disciplinary areas such as web development, data structures and mathematical communication, and mathematical modelling.

In third year you'll combine study and hands-on experience with courses in programming and networking, project management, and analytics. You will also complete an ICT industry-based project to strengthen your abilities in research, analysis, and interpretation of data.

You can gain an extra qualification and broaden your career prospects by completing a Diploma in Languages.

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

If you think you might be interested in secondary school teaching, you can apply for the Bachelor of Mathematics (Data Science)/Master of Teaching (Secondary), it's a direct pathway into postgraduate study.

1 Deloitte analytics trends 2016