Program Overview

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 insights based on data.

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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  Location

AdelaideAustralia

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  Course Duration

24 Months

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  Tuition Fee

AU$ 36,600

 Score

IELTS: 6.5 TOEFL: 60

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You will start by developing foundation skills in data and statistics and then in second year, you will study advanced skills in analytics. This will include courses such as:
 

  • Predictive Analytics
  • Unsupervised Methods in Analytics
  • Research Methods
  • Data Visualisation
  • Customer Analytics in Large Organisations
  • Advanced Analytic Techniques 1 & 2
  • Social Media Data Analytics


You’ll finish your degree with a professional project where you’ll work in a structured project team, getting practical experience in modern data science techniques and practices.

Degree structure

Semester 1
 

  • Big Data Concepts
  • Statistical Programming for Data Science
  • Statistics for Data Science


Semester 2
 

  • Predictive Analytics
  • Unsupervised Methods in Analytics
  • Research Methods
  • Data Visualisation


Semester 3
 

  • Social Media Data Analytics
  • Customer Analytics in Large Organisations
  • Data Science Professional Development


Semester 4
 

  • Advanced Analytic Techniques 1
  • Advanced Analytic Techniques 2
  • Capstone Professional Project
  • Operations Management Systems
  • Enterprise Resource Management
  • Master Thesis

Applicants to the Master of Data Science will normally have:
 

  • a Bachelor degree or equivalent from a recognised higher education institution with a minimum of one year of full-time study in Mathematics or Information Technology or Data Science or a combination thereof; OR
  • a Graduate Certificate or Graduate Diploma in Data Science or equivalent from a recognised higher education institution.


English language entry requirements

In addition, international students who speak English as a foreign language must have obtained one of the following standards within the last two years prior to admission. Possession of one or more of these qualifications, in addition to the academic entry requirements, does not, in itself, guarantee a place at the University of South Australia. Applications are considered on an individual basis and selection is competitive. Where previous study/work experience was conducted in English, the application must be accompanied by certified documentation from the educational institution/employer certifying that the language of instruction/ employment was English.

English language test
 

  • IELTS total [6.5]
  • IELTS reading [6.0]
  • IELTS writing [6.0]

FEES 

AUD$ 36,600 per annum (per 1.0 EFTSL)

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 world1.

Careers to consider:
 

  • Statistician – As a statistician, your responsibilities include but not limited to is to conduct analyse on data, create projections and interpretations. You will be relied upon to produce statistical inferences based on data collected or available in the organisation.  In addition, you might be responsible for new projects and requesting certain datasets. It will be assumed that you have a strong background in statistics, and can create statistical models and apply techniques to make good business decisions.

  • Data Modeller/Architect – As a data modeller or architect, your responsibilities are concentrated around modelling situations and deducing outcomes by using data. You may be consider an architect in the company since you will build systems both statistically and IT facing to solve problems and model current operations. This will require you to have an in-depth knowledge of databases, predictive analytics and advanced mathematical techniques to solve problems.

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