Outline
Outline
This major is part of the Bachelor of Advanced Science (Honours) course designed for high-performing students to pursue their interest in science through a core of research, leadership and entrepreneurship. The flexible and personalised approach to studying data science enables you to to explore the field through immersive research experiences, industry placement and/or interdisciplinary team-based projects.
In your capstone experience, you'll have the opportunity to pursue data science projects that may be based from pure research through to translational (entrepreneurial) science.
How this course will make you industry ready
The Data Science major develops skills across disciplines and allows students to focus their analytical and data visualisation skills through electives and minor programs.
The course has been developed with industry and is reviewed regularly to ensure that the skills and knowledge are up-to-date and relevant to employers in this dynamic field.
What you'll learn
- Demonstrate an advanced knowledge of the nature of science, its methods and processes, and an advanced knowledge of the theoretical background to processes for efficient collection, management, secure storage and analysis of large data sets.
- Critically analyse challenging and multi-faceted problems in data science, formulating hypotheses about data and developing innovative strategies for testing them; implement appropriate algorithms to analyse both large and small datasets.
- Extract valid and meaningful conclusions from various types of large data sets that can support evidence based decision making, and incorporate them into the planning, conduct and communication of their own work.
- Communicate approaches, ideas, findings and solutions to data science problems in a variety of modes to informed professional audiences.
- Identify, select and use appropriate open source and proprietary data management and analysis tools to identify patterns or relationships in large volumes of data and address complex research questions.
- Demonstrate intellectual independence and engage in self-driven continuous discipline and professional education and training as a data scientist.
- Participate in the generation and application of science in addressing global problems while understanding the global nature of data science; apply appropriate international standards in data science and data analytics.
- Work collaboratively and respectfully with data scientists from a range of cultural backgrounds and understand the importance of the cultural diversity and individual human rights that impact data science.
- Be able to work as an independent data scientist and collaboratively within teams either as a professional leader or collaborator using effective problem solving and decision making skills within a professional context.
