Postgraduate Coursework
Master of Data Science
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
- statistics
- mathematics
- 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.
Professional recognition
The Master of Data Science is accredited by Australia Computer Society at the level of professional and therefore recognised internationally under the Seoul Accord.
Credit transfers and 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
For further information on credit transfer and how to apply visit ASK CDU
International applications
Applications must be submitted online through our application portal, Studylink. You'll need a valid email address to create your online account. Once you have started your application, you will be able to save it and resume it later. There is no application fee when you apply online.
You may be able to lodge a direct application; however, there may be restrictions on your geographic location. If you cannot submit a direct application via the application portal, please apply through one of our registered agents.
Accreditation
This course is accredited by the University in accordance with the Higher Education Standards.
Additional information
Australian qualification framework
This course is recognised in the Australian Qualifications Framework at Level 9.
Contact details
For further information about the course, enrolment procedures, closing dates and other administrative issues please contact Student Central on:
Admission criteria
Successful completion of a recognised bachelor degree or equivalent international qualification.
International Pathway
Applicants who have completed the CDU International Masters Qualifying Program (ZMQP01) or the Accelerated International Masters Qualifying Program (ZAMQP1) are eligible for entry.
Essential requirements
To gain entry into Charles Darwin University, all Higher Education applicants must satisfy the University's English Language Proficiency Requirements for their chosen course of study. International applicants will be required to supply evidence of this at the time of application.
The minimum English language requirement for this course is met by either undertaking previous education in an English-speaking country or undertaking one of the following English language tests and obtaining the minimum requirements listed below.
| IELTS Academic Module | A minimum overall score of 6.5 with no band less than 6.0. |
| Cambridge Advanced English (CAE) | A minimum overall score of 176, with no skill below 169. |
| Common European Framework Certificate of English Proficiency | A minimum overall grade of C1, valid for three years from the date of the test to the date of commencement at CDU. |
| Pearson Test of English (PTE) Academic module | A minimum overall score of 58 with no score lower than 50. |
| TOEFL Internet-based Test (iBT) | A minimum overall score of 79 with a minimum writing score of 21. |
* All tests are valid for two years from the date of the test to the date of commencement at CDU, unless otherwise specified.
* Where applicable, international applicants must also satisfy the Department of Home Affairs (DHA) English language requirements for student visa applications.
Do you have a question regarding English requirements at CDU? Please email: international@cdu.edu.au.
Course structure
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 |
|
Core
|
110cp
|
Compulsory Core units totalling 110 credit points as detailed below:
HIT137 Software Now |
|
Specialist Electives
|
10cp
|
Specialist Elective units totalling 10 credit points selected from one of the options detailed below: BUS501 Decision Making (replaced by BUS508 from 2022) |
| Research Units (2 units)
|
40cp
|
Research totalling 40 credit points as detailed below:
PRT820 Master Thesis x 2 (20cp repeatable unit) |
| Course Total | 160cp |
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.
Study plan
Students commencing in Semester 1
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 | ||
| Year 1 | |||
| 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 |
| Year 2 | |||
| 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 | ||
| Year 1 | |||
| HIT137 Software Now | CO | ||
| HIT140 Foundations of Data Science | CO | ||
| HIT220 Algorithms and Complexity | CO | ||
| Specialist Elective | SE | ||
| Year 2 | |||
| 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 | ||
| Year 3 | |||
| PRT520 Principles of Computing Systems | CO | ||
| PRT574 Security Assessment in Software Development | CO | ||
| PRT820 Master Thesis (20cp) | R | ||
Course fees
Non-Commonwealth supported places
Full fee paying places are available in this course.
2022: Information about fees and charges can be found at Fees and Payments.