Graduate Certificate of Data Analytics
2019 Deakin University Handbook
| Year | 2019 course information |
|---|---|
| Award granted | Graduate Certificate of Data Analytics |
| Course Map |
|
| Campus | Offered at Burwood (Melbourne) |
| Cloud Campus | Yes |
| Duration | 0.5 year full-time or part-time equivalent |
| Deakin course code | S576 |
| Approval status | This course is approved by the University under the Higher Education Standards Framework. |
| Australian Qualifications Framework (AQF) recognition | The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 8. |
INTERNATIONAL STUDENTS – Please note that due to Australian Government regulations, student visas to enter Australia cannot be issued to students who enrol in Deakin’s Cloud Campus. | |
Course sub-headings
- Course overview
- Indicative student workload
- Career opportunities
- Participation requirements
- Mandatory student checks
- Pathways
- Fees and charges
- Course Learning Outcomes
- Course rules
- Course structure
Course overview
The Graduate Certificate of Data Analytics is ideal for students without a computing background, as well as those who’d like to bolster their industry experience with a recognised academic qualification.
With a focus on fundamental data analytics, this course covers foundation skills, security and privacy issues, research and development, and real world analytics. This course gives you the essential skills and knowledge for employment across a range of industries and prepares you for further studies in IT and Data Science.
Units in the course may include assessment hurdle requirements.
Indicative student workload
You can expect to participate in a range of teaching activities each week. This could include classes, seminars, practicals and online interaction. You can refer to the individual unit details in the course structure for more information. You will also need to study and complete assessment tasks in your own time.
Career opportunities
Deakin's Graduate Certificate of Data Analytics prepares students for professional employment across all sectors as data analytics specialists. Data analysts may find employment with organisations who make data-driven decisions, in areas including software development, pharmaceutical discovery, marketing, consulting, manufacturing,
financial services, telecoms, e-commerce, retail, health care, public services, information security and more.
Participation requirements
Reasonable adjustments to participation and other course requirements will be made for students with a disability. Click here for more information.
Mandatory student checks
Any unit which contains work integrated learning, a community placement or interaction with the community may require a police check, Working with Children Check or other check.
Pathways
Further study options:
Upon completion of the Graduate Certificate of Data Analytics, you could use the credit points you’ve earned to enter into further study, including:
S777 Master of Data Science
Fees and charges
Fees and charges vary depending on your course, your fee category and the year you started. To find out about the fees and charges that apply to you, visit www.deakin.edu.au/fees.
Course Learning Outcomes
| Deakin Graduate Learning Outcomes | Course Learning Outcomes |
| Discipline-specific knowledge and capabilities | Develop data analytics solutions based on user requirements by applying foundational knowledge of real world analytics concepts and technologies. |
| Communication | Communicate data analytical solutions as appropriate to the context to inform, motivate and effect change utilising a range of verbal, graphical and written methods, recognising the needs of diverse audiences. |
| Digital literacy | Use digital media to locate and collect information to prepare for data analysis. |
| Critical thinking | Use the frameworks of logical and analytical thinking to evaluate data analytics information and user requirements. |
| Problem solving | Design solutions for automating data analysis processes by applying foundational technical knowledge and tools. |
| Self-management | Demonstrate the ability to work autonomously in order to meet requirements. |
| Teamwork | Not applicable |
| Global citizenship | Engage in professional and ethical behaviour in the collection, processing, and presentation of data. |
Approved by Faculty Board 6 September 2018
Course rules
To complete the Graduate Certificate of Data Analytics, students must attain 4 credit points. Most units (think of units as ‘subjects’) are equal to 1 credit point. So that means in order to gain 4 credit points, you’ll need to study 4 units (AKA ‘subjects’) over your entire degree. Most students choose to study 4 units per trimester, and usually undertake two trimesters each year.
The course comprises a total of 4 credit points, which must include the following:
- Four (4) core Fundamental Data Analytics Studies units (SIT718, SIT719, SIT740, MIS770)(4 credit points)
- Completion of STP050 Academic Integrity (0-credit point compulsory unit)
Students are required to meet the University's academic progress and conduct requirements. Click here for more information.
Course structure
Core
Year 1 - Trimester 1
| STP050 | Academic Integrity (0 credit points) |
| SIT718 | Real World Analytics |
| SIT719 | Security and Privacy Issues in Analytics |
| SIT740 | Research and Development in Information Technology |
| MIS770 | Foundation Skills in Data Analysis |