The Master of Data Science will further develop your technical and analytical skills needed to manage and interpret useful insights from massive data sets.
This qualification complements the following multi-disciplinary areas:
- computer science
- information technology
- information systems
- engineering or a program with substantial quantitative competencies.
Your coursework will also include a project-based assessment allowing you to focus on what you are passionate about.
Graduating from Master of Data Science may lead to career opportunities as a business analyst, data scientist, data analyst, data engineer or data manager.
This course is designed to meet Australian Computer Society requirements at Professional level.
Credit transfers & pathways
Pathways for Higher Education to Higher Education
For information about credit transfer available to students with complete or incomplete study at this or other Institutions refer to Pathways for Higher Education to Higher Education
English Language Requirements for International Students
For detail on English Language Entry Requirements please read the entry requirements provided for International students.
How to Apply
International applicants apply directly to CDU and should refer to the information provided for International future students Apply.
his course is accredited by the University in accordance with the Higher Education Standards.
Australian qualification framework
This course is recognised in the Australian Qualifications Framework at Level 9.
For further information about the course, enrolment procedures, closing dates and other administrative issues please contact Student Central on:
The course consists of core units, thesis research units, specialist elective units and general elective units. The core units of this program will allow you to explore a range of data science concepts.
Research units will allow you to complete an individual research thesis in a chosen area under the guidance of an academic supervisor. The thesis can be carried out within a university, industry, or government setting. Specialist electives will grow your knowledge in areas such as advanced research methods, decision making and biostatistics.
General elective units will allow you to study complimentary courses or explore other areas of interests.
The course stresses both the importance of theory and the application of theory in practice through projects and practical exercises.
You can study a Master of Data Science online or on campus. Access to the internet is required for distance learning, with access to high speed broadband highly recommended.
A candidate must successfully complete units totalling 160 credit points as detailed below. All units are valued at 10 credit points unless indicated.
|Unit type||Credit Points||Specific requirements|
|Compulsory Core units totalling 110 credit points as detailed below:
HIT137 Software Now
Specialist Elective units totalling 10 credit points selected from one of the options detailed below:
|Research totalling 40 credit points as detailed below:
PRT820 Master Thesis x 2 (20cp repeatable unit)
Students who commenced in or after 2013
The grade of "PC" cannot be counted towards a Masters Degree by Coursework AQF Level 9 course award.
Students should refer to the current Grading Policy and Common Course Rules for further information.
The Recommended Study Plan provided below is suitable for a student commencing in semester 1 and enrolling in a standard load. Students entering this course with advanced standing, or wishing to reduce or vary their study plan due to work, personal, financial or other reasons should use the table as a guide to create an individual study plan.
|Legend:||CO = Core Unit||SE = Specialist Elective||R = Research|
|Semester 1||Semester 2|
|HIT234 Database Concepts||CO||HIT137 Software Now||CO|
|PRT520 Principles of Computing Systems||CO||HIT140 Foundations of Data Science||CO|
|PRT531 Business Intelligence and Data Mining||CO||HIT220 Algorithms and Complexity||CO|
|PRT551 Project Management, Risk and Reliability||CO||Specialist Elective||SE|
|PRT564 Data Analytics and Visualisation||CO||PRT563 Advanced Data Management||CO|
|PRT574 Security Assessment in Software Development||CO||PRT565 Machine Learning and Artificial Intelligence||CO|
|PRT820 Master Thesis (20cp)||R||PRT820 Master Thesis (20cp)||R|
Students commencing in Semester 2
The Recommended Study Plan provided below is suitable for a student commencing in semester 2 and enrolling in a standard load. Students entering this course with advanced standing, or wishing to reduce or vary their study plan due to work, personal, financial or other reasons should use the table as a guide to create an individual study plan.
|Semester 1||Semester 2|
|HIT137 Software Now||CO|
|HIT140 Foundations of Data Science||CO|
|HIT220 Algorithms and Complexity||CO|
|HIT234 Database Concepts||CO||PRT563 Advanced Data Management||CO|
|PRT531 Business Intelligence and Data Mining||CO||PRT565 Machine Learning and Artificial Intelligence||CO|
|PRT551 Project Management, Risk and Reliability||CO||PRT820 Master Thesis (20cp)||R|
|PRT564 Data Analytics and Visualisation||CO|
|PRT520 Principles of Computing Systems||CO|
|PRT574 Security Assessment in Software Development||CO|
|PRT820 Master Thesis (20cp)||R|
Non-Commonwealth supported places
International tuition fees
The annual course tuition fee for full time study of 80 credit points for commencing students in 2021 is AUD $29,616.00.
These fees are subject to annual increases each year of your study, effective at the start of each calendar year.
You can find a list of International fees and payments you can expect to pay as part of your studies in Australia.
CDU offers a number of scholarships to international students to assist with the cost of study.