Main navigation
- Programs
- Subjects
- Universities
- Destinations
- Advice
Emphasizes developing graduates' numerical and analytical skills. Students will acquire statistical proficiency for examining and presenting both simple and complex data from diverse sources, including disease indicators, genomic information, transcriptomic datasets, and business analytics. Graduates will be well-prepared to excel in the competitive data science field across computing, business, and scientific sectors.
Learning Outcomes
Utilize comprehensive discipline knowledge to address various big data scenarios, both theoretical and practical.
Evaluate theoretical frameworks and datasets using multiple data science methodologies.
Derive insights from statistical models to develop data-driven solutions.
Employ statistical software and database systems to explore and resolve data science challenges.
Clearly and independently convey data science concepts and findings.
Integrate global viewpoints, including Aboriginal and Torres Strait Islander cultural perspectives, into scientific approaches.
Collaborate effectively while incorporating social, sustainable, and ethical considerations in scientific work.
Apply acquired knowledge to professional settings.