Master of Data Science

Provider:

Swinburne University of Technology (Sydney)

Course Code:

MA-DATASC

CRICOS Code:

099117B

Qualification Level:

Masters, Postgraduate

Course Area:

Information Technology

Duration:

2-Year

Study Mode:

Full Time

Course Fees:

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Delivery Mode:

On Campus

Target:

International

Intake:

February, June, September

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Course Overview

The Master of Data Science is designed to prepare students to work on the forefront of data-driven decision-making and forecasting.

Build on your existing undergraduate qualification and/or industry experience as you develop an in-depth understanding of activities and processes related to managing, interpreting, understanding and deriving knowledge from large data sets.

In this course, you’ll learn how to gain meaningful insight from data obtained from business, government, scientific and other sources. Expand your knowledge and understanding of computer science and data analytics, develop skills in state-of-the-art techniques and contemporary tools covering the entire data management lifecycle.

Course Structure

To qualify for the Master of Data Science, students must complete 200 credit points comprising:

Core Units (175 credit points)

COS60004 Creating Web Applications
COS60008 Introduction to Data Science
COS60009 Data Management for the Big Data Age
COS60010 Technology Enquiry Project
COS60011 Technology Design Project *
COS70004 User-Centred Design
COS70008 Technology Innovation Project *
COS80001 Cloud Computing Architecture
COS80023 Big Data *
COS80025 Data Visualisation
COS80027 Machine Learning *
COS80029 Technology Application Project

Elective Units (25 credit points in total)

COS70006 Object-Oriented Programming
ICT80007 Research Paper
ICT80004 Internship Project

The Graduate Diploma of Data Science is an Exit Award only (not by admission)

Entry Requirement

Admission Requirements
Academic Entry Requirements	The admission requirements for Master of Data Science consist of: a completed bachelor degree (or higher award) in any discipline from a recognised higher education institution or equivalent

Language Requirement
English Language Requirements	International students Satisfactory completion of one of the following: minimum IELTS overall band of 6.5 (Academic Module) with no individual band below 6.0 TOEFL iBT (internet-based) minimum score of 79 with a reading band no less than 18 and writing band no less than 20 Pearson (PTE) minimum score of 58 (no communicative skills less than 50) any other equivalent assessment of English language proficiency.

Language Requirement

English Language Requirements

International students

Satisfactory completion of one of the following:

minimum IELTS overall band of 6.5 (Academic Module) with no individual band below 6.0
TOEFL iBT (internet-based) minimum score of 79 with a reading band no less than 18 and writing band no less than 20
Pearson (PTE) minimum score of 58 (no communicative skills less than 50)
any other equivalent assessment of English language proficiency.

Subjects

Subject Name	Subject Type	Fees
Research paper	Elective
Big Data	Core
Data Visualisation	Core
Machine Learning	Core
Technology Application Project	Core
Internship Project	Elective
Creating Web Applications	Core
Introduction to Data Science	Core
Data Management for the Big Data Age	Core
Technology Enquiry Project	Core
Technology Design Project	Core
User-Centred Design	Core
Object Oriented Programming	Elective
Technology Innovation Project	Core
Cloud Computing Architecture	Core

Career Opportunities

Graduates will have skills in state-of-the-art techniques and experience in contemporary tools covering a variety of aspects of the entire data management lifecycle, allowing them to work on the forefront of data-driven decision making and forecasting.