Course overview

Description

The Master of Business Analytics is relevant for those students looking to draw insights from data to enable better business decisions. In this course students will learn analytical and technical skills and apply these skills to business contexts.

Course title
Master of Business Analytics (coursework)
Award abbreviation
MBusA
Course code
42630
Course type
Master's degree by coursework only
Status
Current / 2023
Administered by
UWA Business School
CRICOS code
0101328

Course details

Intake periods
Beginning of year and mid-year
Attendance type
Full- or part-time (Student visa holders should read Education Services for Overseas Students Act 2000 for more information.)
Credit points required
96
A standard full-time load is 24 points per semester.
Standard course duration
1.5 full-time (or equivalent part-time) comprising 72 points of taught units and 24 points of admission credit, as recognised and granted by the School
Maximum course duration
2.0 full-time (or equivalent part-time) comprising up to 96 points of taught study (see Rule 5 for further information)
Time limit
5 years
Delivery mode
Internal
Locations offered
UWA (Perth)
Domestic fee type
Postgraduate fee-paying/FEE-HELP
Available to international students
Yes. For information on international student fees see 'Student Procedures: Fees'. (Enquiries: https://www.uwa.edu.au/askuwa)
Course Coordinator(s)
Dr Catherine Leighton
Fees
Visit the fees calculator.

Prospective students should see the Future Students website for details on admission requirements, intake periods, fees, availability to international students, careers information etc.

No study plans found for this course. See study plans for more information.

Course structure

Key to availability of units:
S1
Semester 1
S2
Semester 2
N/A
not available in 2023 – may be available in 2024 or 2025

All units have a value of six points unless otherwise stated.

Students who have completed prior tertiary study in data science are not required to complete BUSN5101 Programming for Business and should contact their Student Advising Office for advice.

Students without requisite cognate studies may be required to take units to the value of 24 points as advised by the Faculty.

Take all units from this group (30 points):

AvailabilityUnit codeUnitnameUnit requirementsContact hours
S1, S2BUSN5002Fundamentals of Business Analytics
Prerequisites
Enrollment in 42270 Graduate Certificate in Business Analytics
or 42630 Master of Business Analytics
Standard Semester: lectures/tutorials/seminars/workshops: up to 3 hours per week
S1, S2BUSN5003Data Storytelling
Prerequisites
Enrolment in
42630 Master of Business Analytics
or 41690 Master of Marketing
or 62530 Master of Data Science
or 42270 Graduate Certificate in Business Analytics
Up to three hours per week.
S1, S2BUSN5007Business Analytics Industry Project (12 points)
Prerequisites
Enrolment in
Master of Business Analytics (completion of at least 30 points), including: BUSN5002.
BUSN5003.
BUSN5101 or equivalent.
.
Indicative contact hours: up to 6 hours per week.
S1, S2BUSN5101Programming for Business
Prerequisites
Enrolment in
42270 Graduate Certificate in Business Analytics (ID 1458)
or Course Enrolment 42630 Master of Business Analytics (ID 1478)
or 41670 Master of Business Information and Logistics Management (ID 43)
Incompatibility
CITS1401 Computational Thinking with Python or equivalent.
Standard Semester: lectures/tutorials/seminars/workshops: up to 3 hours per week

Take units to at least the value of 18 points from this group.

Note: Business Applications Units

Group A
AvailabilityUnit codeUnitnameUnit requirementsContact hours
S2BUSN5001Blockchain and Distributed Ledger Technologies in BusinessNoneStandard Semester: lectures/tutorials/seminars/workshops: up to 3 hours per week Summer School: delivered intensively, up to 18 hours per week
S1ECON5514Economic Research and Evaluation Methods
Incompatibility
ECON2271 Introductory Econometrics
seminars: 3 hours per week
S2HRMT5502People Analytics
Prerequisites
Enrolment in
41660 Master of Human Resources and Employment Relations (ID 45)
or Course Enrolment 42270 Graduate Certificate in Business Analytics (ID 1458)
or Course Enrolment 42630 Master of Business Analytics (ID 1478)
or 73550 Master of Business Psychology (ID 1408)
lectures/seminars/workshops: up to 3 hours per week
S2INMT5526Business Intelligence
Prerequisites
INMT5518 Models for Logistics, Operations and Services (ID 3338)
or BUSN5002 Fundamentals of Business Analytics (ID 7181)
or Unit(s) BUSN5101 Programming for Business (ID 7189) or equivalent
lectures/seminars/workshops: up to 3 hours per week
S1MGMT5660Applied Project Management
Incompatibility
MGMT5665 Project Management
lectures/seminars: up to 3 hours per week
S1MKTG5504Big Data in MarketingNoneSeminars: 3 hours per week for 12 weeks.

Take up to the number required to complete course (maximum of 24 points):

Group B
AvailabilityUnit codeUnitnameUnit requirementsContact hours
S1, S2ACCT5432Introductory Financial Accounting
Incompatibility
ACCT1101 Financial Accounting, ACCT5602 Accounting
lectures/seminars/workshops: up to 3 hours per week
S1, S2BUSN5100Applied Professional Business Communications
Incompatibility
WACE/TEE English or equivalent
or BUSN4003 Applied Business Communication
or MGMT5610 Applied Professional Business Communications
lectures/seminars/workshops: up to 3 hours per week
S1CITS4407Open Source Tools and Scripting
Prerequisites
Enrolment in
in the the 62510 Master of Information Technology
or the 62530 Master of Data Science
or the 72530 Master of Environmental Science
or the 42630 Master of Business Analytics
S2CITS5503Cloud Computing
Prerequisites

Enrolment in
( HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 42630 Master of Business Analytics
or BH008 Bachelor of Advanced Computer Science [Honours]
or MJD-ICYDM International Cybersecurity
or MJD-CDSDM Computing and Data Science

and 12 points of programming-based units )
or Enrolment in 62550 Master of Professional Engineering Software Engineering specialisation
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 Points
and 12 points of programming-based units
S1CITS5508Machine Learning
Prerequisites
Enrolment in
Computer Science and Software Engineering [Honours]
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 63550 Master of Engineering
or 42630 Master of Business Analytics
or 62550 Master of Professional Engineering
or 53560 Master of Physics (specialised in Medical Physics)
or BH008 Bachelor of Advanced Computer Science [Honours] and the MJD-CDSDM Computing and Data Science major
or the MJD-ARIDM Artificial Intelligence major
) and completion of 12 points of programming-based units
lectures: 2 hours per week; labs: 2 hours per week for 11 weeks from week 2
N/AECON5513Applied Advanced Econometrics
Prerequisites
ECON2271 Business Econometrics or equivalent
lectures/tutorials/seminars/workshops: up to 3 hours per week
S1ECON5520Text-to-Data Applications and Novel Data Sources
Prerequisites
Enrolment in
42630 Master of Business Analytics
or 42620 Master of Economics
or 42670 Master of Economics
or CM002 Bachelor of Economics and Master of Economics
seminars: 3 hours per week for 12 weeks
S2, S1ECON5541Economics for Business: Applications and Policy
Incompatibility
ECON5503 Economic Management and Strategy.
ECON1000 ECON1101 or equivalent.
lectures/seminars/workshops: up to 3 hours per week
S2ECON5570Health Analytics
Prerequisites
Enrolment in
CM002 Bachelor of Economics and Master of Economics
or 42620 Master of Economics
or 42670 Master of Economics
or 42630 Master of Business Analytics
or 42580 Master of Public Policy
seminars: up to 3 hours per week for 12 weeks
S2INMT5501Enterprise Information SystemsNonelectures/seminars/workshops: up to 3 hours per week
S1INMT5518Supply Chain AnalyticsNonelectures/seminars/workshops: up to 3 hours per week
S1, S2MGMT5507Management and Organisations
Incompatibility
MGMT1136 Management and Organisations
lectures/seminars/workshops: up to 3 hours per week
S2MKTG5502Digital MarketingNoneSemester 2: Up to 3 hours per week.

See also the rules for the course and the Student Rules.

Rules

Applicability of the Student Rules, policies and procedures

1.(1) The Student Rules apply to students in this course.

(2) The policy, policy statements and guidance documents and student procedures apply, except as otherwise indicated in the rules for this course.

Academic Conduct Essentials and Communication and Research Skills modules

2.(1) Except as stated in (2), a student who enrols in this course for the first time irrespective of whether they have previously been enrolled in another course of the University, must undertake the Academic Conduct Essentials module (the ACE module).

(2) A student who has previously achieved a result of Ungraded Pass (UP) for the ACE module is not required to repeat the module.

English Language competency requirements

3. To be considered eligible for consideration for admission to this course an applicant must satisfy the University's English language competence requirement as set out in the University Policy on Admission: Coursework.

Admission requirements

4.(1) To be considered for admission to this course an applicant must have—

(a) a Bachelor's degree, or an equivalent qualification incorporating at least one unit of statistics, as recognised by UWA; and either:

(b) the equivalent of a UWA weighted average mark of at least 50 per cent;

or

(c) at least two years professional experience in a relevant occupation; or

(2) completed a Graduate Certificate in Business Analytics at UWA.

Admission ranking and selection

5. Where relevant, admission will be awarded to the highest ranked applicants or applicants selected based on the relevant requirements.

Articulations and exit awards

6.(1) The following courses form part of an articulated sequence:

  • 42270 Graduate Certificate in Business Analytics (24 points)
  • 42630 Master of Business Analytics (96 points)

(2) A student who withdraws from the Master of Business Analytics course before completing it, but after fulfilling the requirements of a lesser award in the above sequence, may apply for the relevant award.

Course structure

7.(1) The course consists of units to a total value of 96 points (maximum value) which include conversion units to a value of 24 points.

(2) Units must be selected in accordance with the course structure, as set out in these rules.

(3) Students who have completed a bachelor's degree with a major in a Commerce-related discipline, or a major in a Computer Science discipline (including a statistics unit), or equivalent as recognised by the Faculty are granted credit for conversion units up to a value of 24 points.

Satisfactory progress

8. To make satisfactory progress a student must pass units to a point value greater than half the total value of units in which they remain enrolled after the final date for withdrawal without academic penalty.

9. A student who has not achieved a result of Ungraded Pass (UP) for the Communication and Research Skills module (the CARS module) when their progress status is assessed will not have made satisfactory progress even if they have met the other requirements for satisfactory progress in Rule 8.

Progress status

10.(1) A student who makes satisfactory progress in terms of Rule 8 is assigned the status of 'Good Standing'.

(2) Unless the relevant board determines otherwise because of exceptional circumstances—

(a) a student who does not make satisfactory progress for the first time under Rule 8 is assigned a progress status of 'On Probation';

(b) a student who does not make satisfactory progress for the second time under Rule 8 is assigned a progress status of 'Suspended';

(c) a student who does not make satisfactory progress for the third time under Rule 8 is assigned a progress status of 'Excluded'.

11. A student who does not make satisfactory progress in terms of Rule 9 is assigned the progress status of 'On Probation', unless they have been assigned a progress status of 'Suspended' or 'Excluded' for failure to meet other satisfactory progress requirements in Rule 8.

Award with distinction

12. To be awarded the degree with distinction a student must achieve a course weighted average mark (WAM) of at least 80 per cent which is calculated based on—

(a) all units above Level 3 attempted as part of the course that are awarded a final percentage mark;

(b) all relevant units above Level 3 undertaken in articulating courses of this University that are awarded a final percentage mark;

and

(c) all units above Level 3 completed at this University that are credited to the master's degree course.

Deferrals

13. Applicants awarded admission to the course are entitled to a deferral of up to 12 months, as per the University Policy on: Admissions (Coursework).