Master of Data Science (MADS)

Information Technology
MDSc

Master of Data Science (MADS) - MDSc

CRICOS code (International applicants): 0101854

	On-campus	Online
Start:	Semester 1 (February) Semester 2 (July) Semester 3 (November)	Semester 1 (February) Semester 2 (July) Semester 3 (November)
Campus:	Toowoomba	-
Fees:	Commonwealth supported place Domestic full fee paying place International full fee paying place	Commonwealth supported place Domestic full fee paying place International full fee paying place
Standard duration:	2 years full-time, 4 years part-time

Contact us

Future Australian and New Zealand students	Future International students	Current students
Freecall (within Australia): 1800 269 500 Phone (from outside Australia): +61 7 4631 5315 Email: study@usq.edu.au	Phone: +61 7 4631 5543 Email: international@usq.edu.au	Freecall (within Australia): 1800 007 252 Phone (from outside Australia): +61 7 4631 2285 Email: usq.support@usq.edu.au

Program aims

With the popularity of social media and the wide spread use of the Internet, enormous amounts of data of various types are generated at all times. The Master of Data Science is designed to provide an opportunity for graduates from all disciplines to gain advanced skills and knowledge in handling data more commonly known as Big Data, as well as producing and interpreting data analytics. The aim of this program is to provide students with a career path in Data Science and an opportunity for advancement in their career.

Program objectives

On completion of the program students should be able to:

Autonomously apply key ICT and data science professional knowledge, technologies and programming skills to critically investigate and analyse contemporary core issues in a global market, and to develop big data analysis and evidence-based decision-making skills.
Select, adapt and apply specialised quantitative and technical skills to work independently and collaboratively to process and interpret major theories and concepts associated with big data to solve and interpret complex and real-life problems.
Work under broad direction within a team environment, manage conflict, and take a leadership role for a task within the project.
Apply and communicate ethical, legal, and professional standards related to big data privacy and building of a security culture, and assess and evaluate risks in order to comply with customer organisational requirements.
Investigate, critically analyse, evaluate and communicate research findings and problem solutions associated with applied data theories and methodologies to specialist and non-specialist audiences.

Australian Qualifications Framework

The Australian Qualifications Framework (AQF) is a single national, comprehensive system of qualifications offered by higher education institutions (including universities), vocational education and training institutions and secondary schools. Each AQF qualification has a set of descriptors which define the type and complexity of knowledge, skills and application of knowledge and skills that a graduate who has been awarded that qualification has attained, and the typical volume of learning associated with that qualification type.

This program is at AQF Qualification Level 09. Graduates at this level will have specialised knowledge and skills for research, and/or professional practice and/or further learning.

The full set of levels criteria and qualification type descriptors can be found by visiting .

Admission requirements

To be eligible for admission, applicants must satisfy the following requirements:

Completion of an Australian university three year Bachelor degree in any area, or equivalent OR
A minimum of five years’ professional work experience equivalent to a qualification at AQF Level 7.
English Language Proficiency requirements for Category 2.

All students are required to satisfy the applicable .

If students do not meet the English language requirements they may apply to study a ��ýapp-approved . On successful completion of the English language program, students may be admitted to an award program.

Program fees

Commonwealth supported place

A Commonwealth supported place is where the Australian Government makes a contribution towards the cost of a students' higher education and students pay a , which varies depending on the courses undertaken. Students are able to calculate the fees for a particular course via the .

Commonwealth Supported students may be eligible to defer their fees through a Government loan called .

Domestic full fee paying place

Domestic full fee paying places are funded entirely through the full fees paid by the student. Full fees vary depending on the courses that are taken. Students are able to calculate the fees for a particular course via the

Domestic full fee paying students may be eligible to defer their fees through a Government loan called provided they meet the residency and citizenship requirements.

Australian citizens, Permanent Humanitarian Visa holders, Permanent Resident visa holders and New Zealand citizens who will be resident outside Australia for the duration of their program pay full tuition fees and are not eligible for .

International full fee paying place

International students pay full fees. Full fees vary depending on the courses that are taken and whether they are studied on-campus, via distance education/online. Students are able to calculate the fees for a particular course via the .

Program structure

The program consists of 16 units comprising of:

12 units of 11 ICT courses and 1 approved course; and
4 units in either:

Research training track of ; ; ; and 1 approved course; or

Research project track of and or and .

Research Project Track

Normally these research project courses are undertaken in the latter stages of candidature. Students must have approval of the Program Director and a Supervisor prior to undertaking this track, which is dependent on the availability of supervisors and resources.

Students may, with approval of the Program Director and acceptance by an appropriate supervisor, elect to replace two or four units of research training courses (, , and/or one approved course.) with one or two 2-unit research project courses ( and ).

Students who have completed in their Bachelor’s degree will undertake an alternative course to .

Courses	Semester of offer Online	Semester of offer Toowoomba campus	Semester of offer Springfield campus
	1,2 3	1,2 3	1,2
	1,2 3	1	1
	1	1
	1,2	1	1
	1,2	1,2
	2,3	2	2
	2,3	2
	1	1
	1	1
	1,2	1,2
	1,2	1,2
1 x Approved course
and EITHER the following four courses, which comprise the Research Training Track:
	1,2
	1,2
	1,2	1,2
1 x Approved course
OR the following two courses (subject to prior approval), which comprise the Research Project Track:
^*	1,2	1,2
^*	1,2	1,2
OR (instead of MSC8001 and MSC8002):
^*	1	1,2
^*	2	2

Footnotes
*	Two-unit course.

Approved Courses

More approved courses from other disciplines may be available after consultation with the Program Director via usq.support@usq.edu.au

Semester 1	Semester 2	Semester 3
Agriculture Discipline Approved Courses

^##
Astrophysics Discipline Approved Courses
Compulsory initial course:
^*^##
Plus any one from the following:
^*^##	^*^##
	^*^##
Business Discipline Approved Courses
CIS8702 Crypto-currencies

Computing Discipline Approved Courses
^**	^**
^**	^**
^**^@	^**
^**	^**
^**	^**
^**	^**^@
^**	^**
CSC8503 Principles of Programming Languages^**	CSC8420 Mobile Systems^**
	^**
	CSC8415 Computer Network Programming^**
	^**
Information Systems Discipline Approved Courses








Mathematics Discipline Approved Courses
^**	^**
^**	^**
^**	^**
Statistics Discipline Approved Courses
^**	^**
^**	^**
^**	^**

Footnotes
##	Online offer only
*	Two unit course
**	Enrolment in this course is subject to having the correct prerequisites or equivalent.
@	The CISCO certificate training is only available in ONC mode. Students who seek the certificate should enrol in ONC mode and be able to attend compulsory weekly workshops at Toowoomba campus.

Required time limits

Students have a maximum of six years to complete this program.

Articulation

Students completing the research project track within the Master of Data Science would be eligible to apply for articulation to the Master of Science (Research) or Doctor of Philosophy programs if they meet other requirements for entry into those programs. Students completing the research training track within the Master of Data Science with the appropriate GPA would be eligible to apply for enrolment in the Master of Science (Research) (Advanced) and then could progress (articulate) to a Doctor of Philosophy via that route once they have demonstrated satisfactory progress in a significant research component.

Exit points

Students may exit with the Graduate Diploma of Science (Applied Data Science) on successful completion of at least eight courses within the Master of Data Science if they have satisfied the requirements of a Graduate Diploma of Science (Applied Data Science). Students may exit with the Graduate Diploma of Science (General) if they have completed at least eight courses from the Master of Data Science, including four post-graduate courses coded at 5000 level or above.

Students may exit with the Graduate Certificate of Science (Applied Data Science) on successful completion of at least four courses within the Master of Data Science if they have satisfied the requirements of a GCSC Graduate Certificate of Science (Applied Data Science). Students may exit with the Graduate Certificate of Science (General) if they have completed at least four courses from the Master of Data Science, including at least two courses coded at 5000 level or above.

Credit

Exemptions/credit for all specialisations will be assessed according to .

Up to four units of coursework exemptions or credit will be granted if the student has completed courses equivalent to courses offered in the Master of Data Science in either:
- USQ's Graduate Certificate of Science; or
- A Graduate Diploma or Bachelor’s Honours Degree qualification in a discipline different from the current area of study.
Up to eight units of coursework credit or exemptions will be granted if the student has completed courses equivalent to courses offered in the Master of Data Science in either:
- USQ's Graduate Diploma of Science; or
- A Graduate Diploma or Bachelor’s Honours Degree qualification in a discipline equivalent to the current area of study.

Notes:

All requests for credits or exemptions need to be sought by the student and approved by the Program Director.
The Program Director will deem to what extent prior studies are equivalent.

Enrolment

Recommended enrolment patterns

In this section:

Recommended Enrolment Pattern - Full-time (4 Semesters, S1 entry)
Recommended Enrolment Pattern - Part-time (8 Semesters, S1 entry)
Recommended Enrolment Pattern - Full-time (4 Semesters, S2 entry)
Recommended Enrolment Pattern - Full-time (S3 entry)

Recommended Enrolment Pattern - Full-time (4 Semesters, S1 entry)

Students are able to enrol in any offered mode of a course (on-campus, external or online), regardless of the program mode of study they enrolled in.

Students may, with approval of the Program Director and acceptance by an appropriate supervisor, elect to replace two or four units of research training courses (, , and/or 1 approved course) with one or two 2-unit research project courses ( and ) or ( and ).

Course	Year of program and semester in which course is normally studied						Enrolment requirements
	On-campus (ONC)		External (EXT)		Online (ONL)
	Year	Sem	Year	Sem	Year	Sem
Year 1 Semester 1
	1	1,2			1	1,2
	1	1			1	1	Enrolment is not permitted in if CIS8701 has been previously completed.
	1	1			1	1	Enrolment is not permitted in if has been previously completed.
	1	1,2,3			1	1,2,3
Year 1 Semester 2
^**					1	2
	1	2			1	2	Pre-requisite or Co-requisite: and ( or ) or equivalent program and statistical knowledge and skills.
	1	2			1	2	Pre-requisite: ( or ) and or equivalent program and statistical knowledge and skills.
^**					1	2	Enrolment is not permitted in if CIS8010 has been previously completed.
Year 2 Semester 1
	2	1			2	1	Pre-requisite or Co-requisite: or
	2	1			2	1	Pre-requisite: ( or ) and
Either the following two courses for the Research Training Track
	2	1			2	1	Pre-requisite: Students must be enrolled in one of the following programs: MSCN or MSCR or MCTN or MADS or GCSC or GDSI or DPHD or its equivalent. Enrolment is not permitted in if has been previously completed.
Approved Course^{^}	2	1			2	1
or one of the following courses for the Research Project Track (if approved instead of Research Training Track)
^*	2	1			2	1	Pre-requisite: Students must be enrolled in one of the following Programs: MCTN or MCOP or MCTE or MSCN or MCCO or MADS or have the approval of their program coordinator
or
^*	2	1			2	1	Pre-requisite: Students must be enrolled in one of the following programs: MSCN or MADS
Year 2 Semester 2
	2	2			2	2	Pre-requisite: CIS8010 or and Students must be enrolled in one of the following Programs: MCTN or MCOP or MSCN (Applied Data Science) or MADS
Approved Course^{^}	2	2			2	2
Either the following two courses for the Research Training Track
					2	1,2
					2	1,2
or one of the following courses for the Research Project Track (if approved instead of Research Training Track)
^*	2	2			2	2	Pre-requisite:
or
^*	2	2			2	2	Pre-requisite:

Footnotes
**	This course is offered online only in Semester 2, 2020.
^	For a comprehensive list of Approved Courses, refer to Program Structure Section.
*	Two unit course

Recommended Enrolment Pattern - Part-time (8 Semesters, S1 entry)

Students are able to enrol in any offered mode of a course (on-campus, external or online), regardless of the program mode of study they enrolled in.

Course	Year of program and semester in which course is normally studied						Enrolment requirements
	On-campus (ONC)		External (EXT)		Online (ONL)
	Year	Sem	Year	Sem	Year	Sem
Year 1
	1	1,2			1	1,2
	1	1			1	1	Enrolment is not permitted in if has been previously completed.
	1	1,2,3			1	1,2,3
	1	2			1	2	Pre-requisite or Co-requisite: and ( or ) or equivalent program and statistical knowledge and skills.
Year 2
	2	1			2	1	Enrolment is not permitted in if CIS8701 has been previously completed.
	2	1			2	1,2
	2	2			2	2	Pre-requisite: ( or ) and or equivalent program and statistical knowledge and skills.
^**					2	2	Enrolment is not permitted in if CIS8010 has been previously completed.
Year 3
	3	1			3	1	Pre-requisite or Co-requisite: or
	3	1			3	1	Pre-requisite: ( or ) and
	3	2			3	2	Pre-requisite: CIS8010 or and Students must be enrolled in one of the following Programs: MCTN or MCOP or MSCN (Applied Data Science) or MADS
Approved Course^{^}	3	2			3	2
Year 4
Either the following two courses for the Research Training Track
	4	1			4	1	Pre-requisite: Students must be enrolled in one of the following programs: MSCN or MSCR or MCTN or MADS or GCSC or GDSI or DPHD or its equivalent. Enrolment is not permitted in if has been previously completed.
					4	1,2
or one of the following courses for the Research Project Track (if approved instead of Research Training Track)
^*	4	1			4	1	Pre-requisite: Students must be enrolled in one of the following Programs: MCTN or MCOP or MCTE or MSCN or MCCO or MADS or have the approval of their program coordinator
or
^*	4	1			4	1	Pre-requisite: Students must be enrolled in one of the following programs: MSCN or MADS
Either the following two courses for the Research Training Track
					4	1,2
Approved Course^{^}	4	2			4	2
or one of the following courses for the Research Project Track (if approved instead of Research Training Track)
^*	4	2			4	2	Pre-requisite:
or
^*	4	2			4	2	Pre-requisite:

Footnotes
**	This course is only offered online in S2, 2020.
^	For a comprehensive list of Approved Courses, refer to Program Structure Section.
*	Two unit course

Recommended Enrolment Pattern - Full-time (4 Semesters, S2 entry)

Students are able to enrol in any offered mode of a course (on-campus, external or online), regardless of the program mode of study they enrolled in.

Course	Year of program and semester in which course is normally studied						Enrolment requirements
	On-campus (ONC)		External (EXT)		Online (ONL)
	Year	Sem	Year	Sem	Year	Sem
Year 1 Semester 2
	1	1,2,3			1	1,2,3
^**					1	2
^**					1	2	Enrolment is not permitted in if CIS8010 has been previously completed.
	1	1,2			1	1,2
Year 1 Semester 1
	1	1			1	1	Enrolment is not permitted in if has been previously completed.
	1	1			1	1	Enrolment is not permitted in if CIS8701 has been previously completed.
	1	1			1	1	Pre-requisite: ( or ) and
Approved Course^{^}	1	1			1	1
Year 2 Semester 2
	2	2			2	2	Pre-requisite or Co-requisite: and ( or ) or equivalent program and statistical knowledge and skills.
	2	2			2	2	Pre-requisite: ( or ) and or equivalent program and statistical knowledge and skills.
Either the following two courses for the Research Training Track
					2	1,2
					2	1,2
or one of the following courses for the Research Project Track (if approved instead of Research Training Track)
^*	2	2			2	2	Pre-requisite: Students must be enrolled in one of the following Programs: MCTN or MCOP or MCTE or MSCN or MCCO or MADS or have the approval of their program coordinator
or
^*	2	2					Pre-requisite: Students must be enrolled in one of the following programs: MSCN or MADS
Year 2 Semester 1
	2	1			2	1	Pre-requisite or Co-requisite: or
	2	1			2	1	Pre-requisite: CIS8010 or and Students must be enrolled in one of the following Programs: MCTN or MCOP or MSCN (Applied Data Science) or MADS
Either the following two courses for the Research Training Track
	2	1			2	1	Pre-requisite: Students must be enrolled in one of the following programs: MSCN or MSCR or MCTN or MADS or GCSC or GDSI or DPHD or its equivalent. Enrolment is not permitted in if has been previously completed.
Approved Course^{^}	2	1			2	1
or one of the following courses for the Research Project Track (if approved instead of Research Training Track)
^*	2	1			2	1	Pre-requisite:
or
^*	2	1			2	1	Pre-requisite:

Footnotes
**	This course is offered online only in Semester 2, 2020.
^	For a comprehensive list of Approved Courses, refer to Program Structure Section.
*	Two unit course

Recommended Enrolment Pattern - Full-time (S3 entry)

Students are able to enrol in any offered mode of a course (on-campus, external or online), regardless of the program mode of study they enrolled in.

International students may not be able to enrol in 4 courses for a full time workload in Semester 3.

Course	Year of program and semester in which course is normally studied						Enrolment requirements
	On-campus (ONC)		External (EXT)		Online (ONL)
	Year	Sem	Year	Sem	Year	Sem
Year 1 Semester 3
	1	3			1	3
					1	3	Enrolment is not permitted in if CIS8010 has been previously completed.
Year 1 Semester 1
	1	1			1	1
	1	1			1	1	Enrolment is not permitted in if CIS8701 has been previously completed.
	1	1			1	1	Enrolment is not permitted in if has been previously completed.
	1	1			1	1
Year 1 Semester 2
	1	2			1	2	Pre-requisite: CIS8010 or and Students must be enrolled in one of the following Programs: MCTN or MCOP or MSCN (Applied Data Science) or MADS
	1	2			1	2	Pre-requisite or Co-requisite: and ( or ) or equivalent program and statistical knowledge and skills.
	1	2			1	2	Pre-requisite: ( or ) and or equivalent program and statistical knowledge and skills.
Approved Course^{^}	1	2			1	2
Year 2 Semester 1
	2	1			2	1	Pre-requisite: ( or ) and
	2	1			2	1	Pre-requisite or Co-requisite: or
Either the following two courses for the Research Training Track
					2	1
					2	1
or one of the following courses for the Research Project Track (if approved instead of Research Training Track)
^*	2	1			2	1	Pre-requisite: Students must be enrolled in one of the following Programs: MCTN or MCOP or MCTE or MSCN or MCCO or MADS or have the approval of their program coordinator
or
^*	2	1			2	1	Pre-requisite: Students must be enrolled in one of the following programs: MSCN or MADS
Year 2 Semester 2
Either the following two courses for the Research Training Track
	2	2			2	2	Pre-requisite: Students must be enrolled in one of the following programs: MSCN or MSCR or MCTN or MADS or GCSC or GDSI or DPHD or its equivalent. Enrolment is not permitted in if has been previously completed.
Approved Course^{^}	2	2			2	2
or one of the following courses for the Research Project Track (if approved instead of Research Training Track)
^*	2	2			2	2	Pre-requisite:
or
^*	2	2			2	2	Pre-requisite:

Footnotes
^	For a comprehensive list of Approved Courses, refer to Program Structure Section.
*	Two unit course

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