科廷科技大学

Data scientists collate and analyse large volumes of data and communicate their findings to a range of audiences. Their ability to use big data to predict future trends is becoming an essential part of decision making in business and government.

Data is being generated at an unprecedented rate and its availability will continue to increase. Every industry is using large volumes of data – from predicting weather patterns and optimising harvesting in agriculture, to improving patient diagnosis in the health industry, to enhancing the management of remote infrastructure in mining.

This is a multidisciplinary major. It combines studies in computing, emerging internet technologies, media and statistics. You will gain a foundation in programming and statistics, which will form the basis of higher-level studies in data mining, data security and computer simulation.

This course builds your capacity to extract, analyse and visualise large volumes of data and communicate analytical outcomes to a range of audiences. You will graduate equipped to enter a range of industries where data science is key to innovation.

In keeping with Curtin’s strong links with industry, this course has an industry advisory group that provides guidance about the course content. The group comprises representatives from the resources sector, management consulting, data analytics services and spatial data product developers, and enterprises such as Optika Solutions and PwC.

Career information

Careers

Data analyst
Data scientist

Industries

Agriculture and environment
Arts
Economics, business, banking and finance
Geographic information science
Government
Health science
Media
Supply chain logistics
Technology

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.