Graduate Certificate of Data Science
Deakin University
About
The Graduate Certificate of Data Science covers modern data science concepts, statistical data analysis, descriptive analytics and machine learning to equip you with the theory, methodologies, techniques and tools of modern data science and the ability to confidently work with any type of data, to identify trends, make predictions, draw conclusions, drive innovations, make decisions, and to share information that influences people.
Structure
To complete the Graduate Certificate of Data Science, 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 Introductory Data Science Studies units (SIT720, SIT741, SIT742, MIS771) (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.
Entry requirements
Entry requirements
Entry information
Deakin University offers admission to postgraduate courses through a number of Admission categories.
All applicants must meet the minimum English language requirements.
Please note that meeting the minimum admission requirements does not guarantee selection, which is based on merit, likelihood of success and availability of places in the course.
For more information on the Admission Criteria and Selection (Higher Education Courses) Policy visit the Deakin Policy Library
Entry will be based on performance in:
- Bachelor's degree (AQF7) in a related discipline; OR
- 2 years relevant work experience; OR
- Graduate Certificate of Data Analytics (or equivalent); OR
- Evidence of academic capability judged to be equivalent.
Learning outcomes
Deakin's graduate learning outcomes describe the knowledge and capabilities graduates can demonstrate at the completion of their course. These outcomes mean that regardless of the Deakin course you undertake, you can rest assured your degree will teach you the skills and professional attributes that employers value. They'll set you up to learn and work effectively in the future.
| outcome type | outcome description |
|---|---|
| Discipline-specific knowledge and capabilities | Develop data analytics solutions based on user requirements by applying coherent knowledge of the analytics discipline using various machine learning and big data analytics tools and techniques.Apply statistical analysis and visualisation techniques appropriately to interpret analytics outcomes. |
| Communication | Communicate effectively in order to design, evaluate and respond to a range of data analytics problems and utilise a range of verbal, graphical and written forms, customised for diverse audiences. |
| Digital literacy | Utilise a range of digital technologies and information sources to discover, select, analyse, evaluate and disseminate both technical and professional information. |
| Critical thinking | Appraise information using logical and analytical thinking to identify user requirements and propose appropriate solutions. |
| Problem solving | Design solutions for automating data analysis processes by applying foundational technical knowledge and tools. |
| Self-management | Work autonomously and responsibly to create solutions to user problems and actively apply fundamental knowledge of data science and methodologies to meet user requirements. |
| Teamwork | Work independently and collaboratively towards achieving the outcomes of a group project. |
| Global citizenship | Engage in professional and ethical behaviour in the collection, processing, and presentation of data. |
Institution
