Master of Business Analytics (coursework) (42630)
The University of Western Australia
About
UWA's admission requirements for some postgraduate courses have changed for Semester 2, 2020 to facilitate student access to study during the COVID-19 situation.
In many cases, these changes may not be extended beyond 2020.
Contact Future Students for more information.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.
Structure
| KEY TO AVAILABILITY OF UNITS: |
|---|
| S1 = Semester 1; S2 = Semester 2; SS = summer teaching period; NS = non-standard teaching period |
All units have a value of six points unless otherwise stated.
Students without requisite cognate studies may be required to take units to the value of 24points as advised by the Faculty.
Take all units from this group (24 points):
| AVAILABILITY | UNITCODE | UNITNAME | UNIT REQUIREMENTS | CONTACT HOURS |
|---|---|---|---|---|
| S1, S2 | BUSN5002 | Fundamentals 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 |
| S2 | BUSN5003 | Data Storytelling | Prerequisites: Enrolment in Master of Business Analytics, and BUSN5002 Fundamentals of Business Analytics | Up to three hours per week. |
| S2 | BUSN5007 | Business 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. |
Take units to at least the value of 18 points from this group.
Note: Business Applications Units
Group A
| AVAILABILITY | UNITCODE | UNITNAME | UNIT REQUIREMENTS | CONTACT HOURS |
|---|---|---|---|---|
| S2, SS | BUSN5001 | Blockchain and Distributed Ledger Technologies in Business | Standard Semester: lectures/tutorials/seminars/workshops: up to 3 hours per week Summer School: delivered intensively, up to 18 hours per week | |
| S1 | ECON5514 | Economic Research and Evaluation Methods | seminars: 3 hours per week | |
| S1, S2 | HRMT5502 | People Analytics | lectures/seminars/workshops: up to 3 hours per week | |
| S2 | INMT5526 | Business Intelligence | Prerequisites: For Master of Business Analytics students: BUSN5101 Programming for Business | lectures/seminars/workshops: up to 3 hours per week |
| S1 | MKTG5504 | Big Data in Marketing | Seminars: 3 hours per week for 12 weeks. |
Take up to the number required to complete course (maximum of 30 points):
Group B
| AVAILABILITY | UNITCODE | UNITNAME | UNIT REQUIREMENTS | CONTACT HOURS |
|---|---|---|---|---|
| NS, S1, S2 | ACCT5432 | Introductory Financial Accounting | Incompatibility: ACCT1101 Financial Accounting, ACCT5602 Accounting | lectures/seminars/workshops: up to 3 hours per week |
| S1, S2 | BUSN5100 | Applied 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 |
| S1, S2 | BUSN5101 | Programming for Business | Prerequisites: BUSN5002 Fundamentals of Business Analytics Incompatibility: CITS1401 Computational Thinking with Python or equivalent. | Standard Semester: lectures/tutorials/seminars/workshops: up to 3 hours per week |
| S1 | CITS4407 | Open Source Tools and Scripting | Prerequisites: Enrolment in 62530 Master of Data Science or 62510 Master of Information Technology or 42630 Master of Business Analytics. | |
| S2 | CITS5503 | Cloud Computing | Prerequisites: Enrolment in 62530 Master of Data Science or 62510 Master of Information Technology or 62550 Master of Professional Engineering (Software Engineering specialisation) or HON-CMSSE Computer Science and Software Engineering [Honours] or 42630 Master of Business Analytics and completion of 12 points of programming-based units | |
| S1 | CITS5504 | Data Warehousing | Prerequisites: Enrolment in (62530 Master of Data Science or 62510 Master of Information Technology or 42630 Master of Business Analytics) and (CITS1402 Relational Database Management Systems or BUSN5101 Programming for Business or BUSN5002 Fundamentals of Business Analytics). Incompatibility: CITS4243 Advanced Databases, CITS3401 Data Warehousing and Data Mining (formerly CITS3401 Data Exploration and Mining) | lectures: 2 hours per week; labs: 2 hours per week |
| S1 | CITS5508 | Machine Learning | Prerequisites: Enrolment in 62530 Master of Data Science or 62510 Master of Information Technology or 62550 Master of Professional Engineering (Software Engineering specialisation) or the HON-CMSSE Computer Science and Software Engineering [Honours] or 42630 Master of Business Analytics 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 |
| S2 | ECON5513 | Applied Advanced Econometrics | Prerequisites: ECON2271 Business Econometrics or equivalent | lectures/tutorials/seminars/workshops: up to 3 hours per week |
| NS, S1, S2 | ECON5541 | Economics for Business: Applications and Policy | Incompatibility: ECON5503 Economic Management and Strategy; ECON1101 or equivalent. | lectures/seminars/workshops: up to 3 hours per week |
| S2 | INMT5501 | Enterprise Information Systems | lectures/seminars/workshops: up to 3 hours per week | |
| S1 | INMT5518 | Models for Logistics, Operations and Services | Prerequisites: For students enrolled in the Masters of Business Analytics: BUSN5002 Fundamentals of Business Analytics | lectures/seminars/workshops: up to 3 hours per week |
| S1, S2 | MGMT5507 | Management and Organisations | Incompatibility: MGMT1136 Management and Organisations | lectures/seminars/workshops: up to 3 hours per week |
| NS, S2 | MKTG5502 | Digital Marketing | Semester 2: Online seminars, 3 hours per week over 12 weeks. Non-standard: Face-to-face seminars, 36 hours in one week. |
See also the rules for the course and the Student Rules.
Entry 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.
Institution
