Master of Data Science

Data is a vital asset valued by virtually every organisation in the world.

It provides the basis for sensible, evidence-based decision making, and the ability to manage and make sense of data is a key skill in the modern workplace.

In the last decade, streams of data of various types have grown in volume and velocity such that they require specialist skills in order to get the most value from them.

Data scientists are responsible for buildng intelligent systems, mastering intuitive proesses and bringing structure to the vast quantities of data to unlock the potential for improvement and competitive advantage.

Course Aims

The Master of Data Science is designed for graduates from all disciplines to complement their existing skills with a solid background in statistics and computer science, preparing them for advanced subjects in these areas along with discipline-specific data science units. The degree provides access to a back-bone of statistics and computer science units, provided within the course.

Learning Outcomes

Upon completion of this course, students will be able to: understand the key tools, methods and theories used in data science to a level of depth and sophistication consistent with advanced professional practice; synthesise information from data and analyse the lifecycle of data within an organisation; apply problem solving skills and advanced knowledge to implement data analysis solutions for real-world problems; communicate effectively with expert and non-expert audiences to understand issues and gather requirements for the development of data analysis strategies and related systems within an organisation; integrate theories and methods related to data science, statistics and software development by planning and executing a research-grounded industry project; evaluate information from a range of sources, such as peer-reviewed literature and technical documentation, to assess current developments in the area of data science; and demonstrate a sophisticated awareness of the ethical and legal issues that relate to the practice of data science.

Graduate Attributes

Knowledge of a Discipline Graduates will understand scientific practice and have sophisticated knowledge of the methods, theories and technologies in data science. Communication Skills Graduates will be able to effectively communicate complex ideas and issues to a variety of audiences in order to implement data analysis solutions and present scientific outcomes. Communication skills are developed through a combination of class participation, independent learning and the completion of a capstone project. Problem Solving Graduates will be able to apply specialist knowledge in areas of data science, statistics and software development to solve challenging problems. Problem solving is embedded throughout the course and rigorously assessed through coursework and open-ended projects. Information Literacy Graduates will be able to evaluate information from a range of sources, including peer-reviewed literature and technical documentation, to develop their insight within the data science discipline. This key attribute is developed through class participation, individual assessment and the execution of project work. Ethical Conduct and Social Responsibility Graduates will have a deep understanding of the ethical responsibilities related to the practice of data science. They will be able to assess the impact of their actions on the community and behave in a socially responsible manner in a professional environment. This awareness is developed incrementally within the course to give graduates an appreciation of the ethical and social issues that surround the different aspects of data science. Lifelong Learning Data Science is a very rapidly expanding field of study. Graduates have the fundamental skills which enable them to supplement their knowledge and adapt to the changes in methodology and technologies. This is taught and practised by providing core skills and exposing students to a variety of technologies, environments and specialised systems. Independence and Collaboration Graduates will have the ability to operate individually with a high level of autonomy and effectively as part of a team. These skills are developed through research-based projects, individual assessment and class participation.