Program Overview

Organisations in every industry are asking big questions. With a Master of Data Science under your belt, you’ll have the skills to help answer them.
 

Data science professionals are in high demand in today's data-driven world. Whether you're already working in data science, or you're ready to make a career change, our Master of Data Science prepares you for a successful career in this exciting field.
 

Designed in collaboration with our industry partners, this degree gives you the knowledge, skills and hands-on experience to transition from university to the workplace. And with two early exit points along the way, you can be sure that every subject is contributing to your career.
 

You'll build fundamental skills in programming, databases, probability, statistics, data exploration and analysis. Got a particular interest in artificial intelligence, bioinformatics or sport analytics? This degree allows you to specialise in these areas and others, such as big data and cloud computing, business applications and data modelling and analytics.

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LocationPin
  Location

MelbourneAustralia

DurationIcon
  Course Duration

24 Months

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  Tuition Fee

AU$ 36,800

 Score

IELTS: 6.5 TOEFL: 79

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Core subjects
 

Core subjects are required subjects in your course. You need to complete these subjects to attain your degree.
 

Subject name

Subject code

Year

Credit points

ACADEMIC INTEGRITY MODULE

LTU0AIM

1

0

DATA EXPLORATION AND ANALYSIS

CSE5DEV

1

15

DATABASE FUNDAMENTALS

CSE4DBF

1

15

INTRODUCTION TO PROGRAMMING

CSE4IP

1

15

MATHEMATICS FOR DATA SCIENCE

MAT4MDS

1

15

PROBABILITY AND STATISTICS FOR DATA SCIENCE

STM4PSD

1

15

PROFESSIONAL PRACTICES AND ENTREPRENEURSHIP IN INFORMATION TECHNOLOGY                

CSE5003

2

15

Prerequisites
 

Successful completion of an Australian bachelor degree (or equivalent).

 

English language requirement
 

6.5 IELTS (Academic) with no individual band less than 6.0.

Annual tuition fee:

A$36,800

After graduation, you could work across a range of industries, including business and finance, science, education, health, and sports.

  • Data scientist

  • Business analyst

  • Health analyst

  • Bioinformatician

  • Machine learning engineer

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