Master of Data Science (Data Analytics)
UniSQ’s Master of Data Science (Data Analytics) provides an opportunity for graduates from all disciplines to gain useful knowledge in Big Data with a specific focus on Data Analytics.
About the Course
UniSQ’s Master of Data Science (Data Analytics) provides an opportunity for graduates from all disciplines to gain useful knowledge in Big Data with a specific focus on Data Analytics. From big data management, machine learning and data mining, to programming and big data visualisation, you will be prepared for a career in a dynamic and fast-paced industry. Work independently and collaboratively to apply key ICT and data science technologies and programming skills to interpret major theories and critically investigate and solve contemporary core issues in a global market.
Course Entry Requirements
- 3-year bachelor degree from an Australian university, or equivalent, in any area; or a minimum of 5 years' professional work experience equivalent to an AQF Level 7 qualification (bachelor).
- There are inherent requirements that must be met in order to successfully complete this degree. Inherent requirements are fundamental skills, capabilities and knowledge that students must be able to demonstrate in order to achieve the essential learning outcomes of the degree, while maintaining the academic integrity of the degree.
- Proof of meeting the English Language Proficiency requirements is also required.
Course Structure
Recommended study pattern
Year 1
- CSC5020 Foundations of Programming
- STA6200 Statistics for Quantitative Researchers
- CSC6004 Data Mining
- CSC6002 Big Data Management
- STA6100 Multivariate Analysis for High-Dimensional Data
- CIS8711 Cloud Security
- CIS5310 IS/ICT Project Management or CSC6003 Machine Learning
- CIS6008 Business Intelligence or CSC6205 Applied Analytics
Year 2
- CSC6001 Data Visualisation
- CSC6003 Machine Learning or CIS5310 IS/ICT Project Management
- CSC6200 Advanced ICT Professional Project
- CSC6205 Applied Analytics or CIS6008 Business Intelligence
- 4 x Electives or MSC6001 Research Project I and MSC6002 Research Project II or SCI6101 Science in Practice, SCI6102 Research Skills, SCI6103 Essentials for Professional Scientists and 1 x Elective
Award requirements
Completion of 16 units as outlined in the Recommended Study Pattern section.
Exit points
Graduate Diploma of Data Science, Graduate Certificate of Data Science.
- Autonomously apply key ICT and data science professional knowledge, technologies, and programming skills to critically investigate and analyse contemporary core issues in a global market, and to develop big data analysis and evidence-based decision-making skills.
- Select, adapt, and apply specialised quantitative and technical skills to work independently and collaboratively to process and interpret major theories and concepts associated with big data to solve and interpret complex and real-life problems.
- Work under broad direction within a team environment, manage conflict, and take a leadership role for a task within the project.
- Apply and communicate ethical, legal, and professional standards related to big data privacy and building of a security culture, and assess and evaluate risks in order to comply with customer organisational requirements.
- Investigate, critically analyse, evaluate, and communicate research findings and problem solutions associated with applied data theories and methodologies to specialist and non-specialist audiences.
