Overview
Overview
Data scientists work at the interface of computing, statistics, visualisation and media to collate and analyse large volumes of data and then communicate findings to a range of audiences. Their ability to leverage big data to predict future trends is becoming an essential part of decision-making in business and government.
This course sits within the double degree combination of Bachelor of Science/Bachelor of Arts, and also the Bachelor of Science/Bachelor of Commerce. Applicants have the choice of which double degree combination they would like to study.
What jobs can the Data Science course lead to?
- Marketing and advertising data analyst
- Pricing or financial analyst
- Game designer
- Health and allied health data analyst
- Business intelligence analyst
- Machine learning specialist
- Information security technologist
- Growth analyst
- IT statistician
What you'll learn
- understand the theoretical background to processes for efficient collection, management, secure storage and analysis of large data sets
- formulate hypotheses about data and develop innovative strategies for testing them by 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
- communicate approaches and solutions to data science problems to a range of audiences in a variety of modes
- identify, select and use appropriate open source and proprietary data management and analysis tools to identify patterns or relationships in large volumes of data
- recognise the importance of continuous learning opportunities in a rapidly developing field and engage in self-driven development as a data scientist
- understand the global nature of data science and apply appropriate international standards in data science and data analytics
- work collaboratively and respectfully with data scientists from a range of cultural backgrounds
- work professionally and ethically on independent data science projects and as a team member working collaboratively to innovative data science solutions