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Master of Data Science
Master of Data Science

Master of Data Science

  • ID:UOSA610131
  • Level:Master's Degree
  • Duration:
  • Intake:
  • Type:Full-time

Fees (AUD)

  • Application Fee:$200.00
  • TuitionFee/Year:$34,800.00
  • LivingFee/Year:$18,000.00
  • InsuranceFee/Year:$530.00
  • Application Fee:$200.00
  • TuitionFee/Year:$34,800.00
  • LivingFee/Year:$18,000.00
  • InsuranceFee/Year:$530.00
Estimated Total/program:
Accept letter

Admission Requirements

Entry requirements

Applicants to the Master of Data Science will normally have:

  • A Bachelor degree in Information Technology, or in Mathematics from a recognised higher education institution; OR
  • A Graduate Certificate in Data Science or Graduate Diploma in Data Science or equivalent from a recognised higher education institution.

English requirements

  • IELTS total 6.5

Course Information

Enter the revolutionary area of big data where there is an acute shortage of data scientists. A recent McKinsey Global Institute report projects a 50 per cent gap between projected demand and supply by 2018.

Vast volumes of data are generated every day around the globe. The need to make sense of it has given rise to the revolutionary area of ‘Big Data’, and to a new career of ‘data scientist’. Data scientists find patterns, making meaning and drawing value from the seeming chaos.

Taught by leading researchers you will learn to analyse and visualise rich data sources, how to spot data trends and to generate data management strategies.

This postgraduate degree is offered as part of a suite of three programs (graduate certificate, graduate diploma and master). Each qualification extends to the next, so you can easily transition to a master level qualification.

If you decide to exit this degree having completed the first four courses you will receive the Graduate Certificate in Data Science. If you have completed the first eight courses you will receive the Graduate Diploma in Data Science.

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Pre Courses

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Pathway 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 organisation. Analytics, science, data, and reasoning are becoming embedded into decision-making processes, every day and everywhere in the business world.

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. geospatial); 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
  • business data analyst: working with stakeholders, analysts and senior management to understand business strategy and the questions that need to be asked; identifying research needs; designing experiments and making recommendations based on results; driving complex analytics projects to support the business
  • information security analyst: reporting and recommendations to prevent security incidents; security control monitoring; implementing new security technology, methods and techniques; championing security best practice; reviewing systems for security risks and compliance issues

Ability to settle

Overseas Student Health Cover

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