Master of Data Science (Artificial Intelligence and Machine Learning)
Study the Artificial Intelligence and Machine Learning specialisation with UniSQ and explore concepts regarding deep learning, natural language processing, information retrieval and knowledge management.
About the Course
Study the Artificial Intelligence and Machine Learning specialisation with UniSQ and explore concepts regarding deep learning, natural language processing, information retrieval and knowledge management. In an increasingly data driven world, it's critical that we can use information retrieval technologies and systems to query and retrieve useful information to support advanced data analytics and inform high-level decision-making. Explore concepts and learning within big data management, machine learning and data mining to ensure you have the knowledge for a career in this dynamic industry.
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. Please read and understand the inherent requirements specific to the Master of Data Science before applying. 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
STA6100 Multivariate Analysis for High-Dimensional Data
CSC6204 Information Retrieval and Knowledge Management
CSC6002 Big Data Management
CSC6003 Machine Learning
CIS5310 IS/ICT Project Management
Year 2
CSC6201 Deep Learning
CSC6202 Natural Language Processing: Techniques and Applications
CSC6203 Intelligent Multimedia (Computer Vision, Audio) Analysis
CSC6200 Advanced ICT Professional Project
4 x Electives or MSC6001 Research Project I and MSC6002 Research Project II or SCI6103 Essentials for Professional Scientists, SCI6102 Research Skills, SCI6101 Science in Practice 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.
On completion of the program, students should be able to:
- 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.
