Program Overview
Data Science Major (BAdvSci) (Honours)
Overview
The Data Science Major (BAdvSci) (Honours) is a multidisciplinary field involving computing, statistics, internet technologies, and media technologies. This major is designed for high-performing students to pursue their interest in data science through an additional focus on research, leadership, and entrepreneurship.
Admission Criteria
ATAR Pathway
- Minimum ATAR: 95
- Essential WACE subjects (prerequisites):
- Mathematics Methods ATAR
- Desirable WACE subjects:
- Mathematics Specialist ATAR
Alternative Pathways
- STAT entry: Not accepted
- TAFE entry: Not accepted
- Higher education course switcher criteria:
- Attained an ATAR of 95; or
- Completed 200 credits over one year, with a course weighted average (CWA) of 80% or higher; and
- Met the prerequisites.
English Requirements
- IELTS Academic (International English Language Testing System):
- Writing: 7.0
- Speaking: 7.0
- Reading: 7.0
- Listening: 7.0
- Overall band score: 7.0
Course Structure
- The course has a semester one intake only.
- The course is reviewed regularly by external advisors to ensure that the course's skills and knowledge content are up-to-date and industry-relevant.
Career Opportunities
- Data analyst
- Data scientist
- Data engineer
- Financial analyst
- Business intelligence analyst
- Bioinformatician
Industries
- Agriculture and environment
- Arts
- Economics, business, banking, and finance
- Geographic information science
- Government
- Health science
- Technology
- Media
- Minerals and mining
- Energy resources
- Supply-chain logistics
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 analyze challenging and multi-faceted problems in data science, formulating hypotheses about data and developing innovative strategies for testing them; implement appropriate algorithms to analyze 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.
Fees and Scholarships
Please view the Bachelor of Advanced Science (Honours) degree for indicative fees.
How to Apply
Please review information on how to apply for the campus of your choice.
Credit for Recognised Learning (CRL)
Finish your course sooner with credit for your previous study or work experience.
Submit an enquiry CRL search
Pathway Finder Tool
Think you don’t have the marks or qualifications to study at Curtin? We have several pathways to help you meet admission. Use our pathway finder to find your best way to studying with us.
Pathway finder tool
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