Master of Taxation

The Master of Taxation (with Data Analytics and Artificial Intelligence) is designed to equip students with the necessary skills and knowledge for a career in professional taxation in the current era of digital transformation.

The course aims to provide students with the required foundations in taxation and related areas, as well as an understanding of the way in which digital technologies, big data, analytics, artificial intelligence and blockchain can support taxation activities and services.

The course is taught by qualified and experienced academic staff active in scholarship and professional development. The course is at the forefront with business applications of digital technologies embedded across the curriculum.

This course contains 22 units in taxation and related fields. All units are weighted at 6 credit points unless otherwise marked "#" which are units weighted at 3 credit points (i.e. half units).

Assumed Knowledge Required

• TACC601 Principles of Accounting
• TECO601 Principles of Economics
• TSTA602 Quantitative Methods for Accounting and Finance
• TFIN601 Corporate Finance

Term 1 Core Subjects

• TLAW601 Australian Commercial Law
• TACC606 Accounting Theory and Application*
• TACC607 Managerial Accounting*
• TTEC615 Human-Computer Interaction

Term 2 Core Units

• TACC605 Corporate Accounting*
• TACC608 Auditing and Assurance Services*
• TLAW602 Australian Taxation Law*
• WBMT02 Taxation Law and Practice in China

Term 3 Core Units

• TLAW604 Current Issues in Taxation*
• TLAW605 Business and Personal Tax Planning*
• WBMT03 International Tax Treaty and Practice
• WBMT04 Tax and Empirical Method

Term 4 Core Units

• TLAW606 International Taxation*
• TTEC609 Big Data Applications in Taxation #
• TTEC610 Data Visualisation and Presentation in Taxation #
• TTEC611 Blockchain Applications in Taxation #
• TTEC612 Artificial Intelligence Applications in Taxation #
• TCAP603 Digitalised Services in Taxation Practice (Capstone)

To qualify for the degree of Master of Taxation (with Data Analytics and Artificial Intelligence), a student with RPL is expected to complete an aggregate of 18 units (96 units of credit). The number of required units will be up to 22 units (120 credit points) if RPL is not awarded.

*Prerequisite/Co-requisite Requirements