Postgraduate Coursework
Graduate Certificate of Data Science
2020
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UDASC1
The Graduate Certificate 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.
Career opportunities
Graduating from this course may lead to careers as a business analyst, data scientist, data analyst, data engineer and data manager.
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
For further information on credit transfer and how to apply visit ASK CDU
Course fees
Non-Commonwealth supported places
Full fee paying places are available in this course.
2019: Information about fees and charges can be found at Fees and Payments and 2019 HE Units and Fees.
2020: Information about fees and charges for 2020 will be published no later than 1 December 2019.
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This course is accredited by the University in accordance with the Higher Education Standards.
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Australian qualification framework
This course is recognised in the Australian Qualifications Framework at Level 8.
Contact details
For further information about the course, enrolment procedures, closing dates and other administrative issues please contact Student Central on:
Course structure
The course consists of core units, specialist elective units and elective units. The core units of the course will allow you to explore a range of data science concepts.
The specialist elective will allow you to study a complimentary unit in an area such as statistics and decision making.
The course stresses both the importance of theory and the application of theory in practice through projects and practical exercises.
- 2020 HE unit offerings will be published on 1 October 2019.
- 2020 HE unit fees will be published no later than 1 December 2019.
- Always refer to the Course Catalogue for the latest information about your course prior to enrolment.
A candidate must successfully complete units totalling 40 credit points (cp) as detailed below. All units are valued at 10 credit points unless indicated.
| Unit type | Credit Points | Specific requirements |
|
Core Units (3 units) |
30cp |
Compulsory Core units totalling 30 credit points as detailed below.
PRT563 Advanced Data Management (replaces PRT561 from 2019) |
|
Specialist Elective (1 unit) |
10cp |
Specialist Elective unit totalling 10 credit points selected from the following units.
BUS501 Decision Making |
| 40cp | Total Credit Points |
Students who commenced in or after 2013
The grade of "PC" cannot be counted towards a Graduate Certificate AQF Level 8 course award.
Students should refer to the current Grading Policy and Common Course Rules for further information.
Study plan
- 2020 HE unit offerings will be published on 1 October 2019.
- 2020 HE unit fees will be published no later than 1 December 2019.
- Always refer to the Course Catalogue for the latest information about your course prior to enrolment.
Students commencing in Semester 1 - Part time
The Recommended Study Plan provided below is suitable for a student commencing in semester 1 and enrolling in a part time 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 |
| Semester 1 | Semester 2 | ||
| Year 1 | |||
| PRT564 Data Analytics and Visualisation (replaces PRT562) | CO | PRT563 Advanced Data Management (replaces PRT561) | CO |
| BIS551 Business Intelligence and Data Mining | CO | Specialist Elective | SE |
Students commencing in Semester 2 – Part time
The Recommended Study Plan provided below is suitable for a student commencing in semester 2 and enrolling in a part time 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 |
Apply to SATAC for postgraduate studies
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