Course CX9 - Master of Data Science | Federation University Handbook

Course overview

This course provides an opportunity for you to develop an advanced understanding of data science by incorporating and interpreting complex information, concepts and theories to relevant disciplines, using data science tools and methods to manage, process, and analyse data. Throughout the course, you will utilise your skills to handle large volumes of data, working with real-time data, cloud computing, unstructured data and statistical models. As a graduate, you may work in data science related areas such as the health care, finance, government administration and IT industries. Consisting of 14 units of study, the Master of Data Science is taught in English and normally takes two years of full-time study or part-time equivalent to complete. Your admission will be based on having completed a previous bachelors level qualification at AQF 7 or equivalent. The course structure includes 11 core units and three elective units. You will be required to complete two 30 credit point project units (60 credit point project in total) which can be used to undertake either an applied industry based project, or complete a research oriented thesis. This course is also available as a graduate certificate and graduate diploma option for domestic and international students.

Institute / school:

Institute of Innovation, Science & Sustainability

Discipline:

Engineering

Study level:

Postgraduate - Coursework

Study load:

Credit points:

240

AQF level:

9 - Masters Degree

Duration (in full time equivalent):

2 years

Domestic students:

International students:

Professional accreditation:

CRICOS code:

118376K

Course coordinator:

Academic requirements

English language requirements

Course rules show the number and type of credit points needed to finish your course. They help you understand what you need to complete to graduate. You’re responsible for following the course rules and completing the right units. You’ll find a recommended sequence of units that meets these course rules in the course structure.

Complete 240 credit points comprising:

225 credit points from Core Units, and
15 credit points from Prescribed Electives

Core Units

Complete exactly 225 credit points from the following:

Code	Title	Credit points
ITECH5207	The Data-Driven Professional	15
DATSC7003	Experiment Design and Visualisation	15
MATHS7002	Computational Methods for Data Analysis	15
ITECH5104	Foundations of Programming (Masters)	15
ITECH5500	Professional Research and Communication	15
ITECH7001	Artificial Intelligence and Machine Learning	15
STATS5000	Statistics and R	15
STATS7101	Regression and Multivariate Data Analysis	15
ITECH7611	Introduction To Cyber Security Fundamentals and Practices	15
ITECH7401	Leadership in IT Project Management	15
ITECH7416	Masters Project 1	15
ITECH7417	Masters Project 2	15
MATHS5000	Mathematics for Data Science	15
COOPI9011	Co-Operative Placement (Information Technology)	30

Prescribed Electives

Complete exactly 15 credit points from the following:

Code	Title	Credit points
ITECH7407	Real Time Analytics	15
ITECH7614	Data Analytics for Cyber Threat Intelligence	15
ITECH7607	Electronic Commerce Security	15
ITECH5403	Comparative Programming Languages	15
GPSIT5010	Digital Transformation: Service Design (Masters)	15

GPSIT5010 Digital Transformation Service Design (Masters) is required as an XPMC unit offered on Melbourne City campus.

Commendation

Counselling

Unsatisfactory

Exclusion / suspension

Final unit supplementary assessment

Students who receive an MF grade in their final Semester may apply to the Course Coordinator within 7 days of the publication of results for supplementary assessment if that unit is the only outstanding unit required to complete the degree and the student has not been found guilty of any form of academic misconduct (e.g. plagiarism, contract cheating, collusion) in that Semester. The highest grade attainable will be a Pass grade.

<a target="_blank" href="https://www.federation.edu.au/students/student-essentials/how-to-enrol/what-to-enrol-in/">Course structures</a> set out the recommended sequence of units for enrolment. It's your responsibility to comply with the course rules and confirm unit availability (which you'll find under 'Offering' in the 'Key information' section of each unit outline). Select the semester you started your course in (not the semester you're enrolling for).

Year 1

Semester 1

ITECH5207

The Data-Driven Professional

Core Units

ITECH5104

Foundations of Programming (Masters)

Core Units

MATHS5000

Mathematics for Data Science

Core Units

ITECH7611

Introduction To Cyber Security Fundamentals and Practices

Core Units

Semester 2

ITECH5500

Professional Research and Communication

Core Units

ITECH7401

Leadership in IT Project Management

Core Units

Prescribed Electives

STATS5000

Statistics and R

Core Units

Year 2

Semester 1

COOPI9011

Co-Operative Placement (Information Technology)

Core Units

ITECH7416

Masters Project 1

Core Units

ITECH7001

Artificial Intelligence and Machine Learning

Core Units

Semester 2

ITECH7417

Masters Project 2

Core Units

MATHS7002

Computational Methods for Data Analysis

Core Units

DATSC7003

Experiment Design and Visualisation

Core Units

STATS7101

Regression and Multivariate Data Analysis

Core Units

Year 1

Semester 2

ITECH5500

Professional Research and Communication

Core Units

ITECH5104

Foundations of Programming (Masters)

Core Units

ITECH5207

The Data-Driven Professional

Core Units

STATS5000

Statistics and R

Core Units

Semester 1

ITECH7001

Artificial Intelligence and Machine Learning

Core Units

ITECH7401

Leadership in IT Project Management

Core Units

MATHS5000

Mathematics for Data Science

Core Units

ITECH7611

Introduction To Cyber Security Fundamentals and Practices

Core Units

Year 2

Semester 2

ITECH7416

Masters Project 1

Core Units

MATHS7002

Computational Methods for Data Analysis

Core Units

DATSC7003

Experiment Design and Visualisation

Core Units

STATS7101

Regression and Multivariate Data Analysis

Core Units

Semester 1

COOPI9011

Co-Operative Placement (Information Technology)

Core Units

ITECH7417

Masters Project 2

Core Units

Prescribed Electives

Upon successful completion of this course, graduates will be able to:

Ref	Outcome

Placement information

Nested qualifications

<ul><li>Upon successful completion of specified units equal to 60 credit points for this course you may exit this course with the following qualification: <a target="_blank" href="/ords/r/curriculum/catalogue/Program?p5_code=CZ4">CZ4 - Graduate Certificate in Data Science</a></li><li>Upon successful completion of specified units equal to 120 credit points for this course you may exit this course with the following qualification: <a target="_blank" href="/ords/r/curriculum/catalogue/Program?p5_code=CY4">CY4 - Graduate Diploma of Data Science</a></li></ul>

Recognition of prior learning

Unit exclusions

Institute / school:

Institute of Innovation, Science & Sustainability

Discipline:

Engineering

Study level:

Postgraduate - Coursework

Study load:

Credit points:

240

AQF level:

9 - Masters Degree

Duration (in full time equivalent):

2 years

Domestic students:

International students:

Professional accreditation:

CRICOS code:

118376K

Course coordinator:

Add Info Static Text

Internal reference: CX9 - C4.10/MK1.2/O3.5/R3.1

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Catalogue Term and Year

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Overview

Key information

Entry requirements

Course rules

Core Units

Complete exactly 225 credit points from the following:

Prescribed Electives

Complete exactly 15 credit points from the following:

Course structure

Course learning outcomes

Course learning outcomes

Placement

Credit, pathways, and recognition of prior learning

Nested qualifications

Recognition of prior learning

Key information

Additional information

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CX9 - Master of Data Science

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CX9 - Master of Data Science

Breadcrumb Type

Catalogue Term and Year

RDS Holder

Parent Region

Overview

Key information

Entry requirements

Domestic students

Applicants with higher education study

International students

Course rules

Course rules

Core Units

Complete exactly 225 credit points from the following:

Prescribed Electives

Complete exactly 15 credit points from the following:

Academic progress regulations

Course structure

Semester 1 Entry

Semester 2 Entry

Course learning outcomes

Course learning outcomes

Placement

Credit, pathways, and recognition of prior learning

Nested qualifications

Recognition of prior learning

Key information

Additional information

Footer

Traditional Custodians

Main Footer

Section 1

Section 3