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.

The Master of Data Science will provide students with the required knowledge and practical skills to analyse and manage data. They will learn how to deal with large and diverse data sets and apply a variety of technologies to extract meaning from them. This course will prepare students to solve complex and challenging problems in science, health, business and beyond, through a combination of engaging coursework subjects and a comprehensive capstone project experience.

The Master of Data Science is an entry-level postgraduate course that complements any existing skill set and provides opportunity to up-skill for positions that have a rigorous quantitative aspect. Graduates from this program will be well-equipped to tackle complex data science challenges and play a leading role in the future development of data science solutions globally.

The Master of Data Science has been granted Professional Level accreditation by the Australian Computer Society and, through the Seoul Accord, is recognised in other countries.

Upon completion of this course, students will be able to:

1. understand the key tools, methods and theories used in data science to a level of depth and sophistication consistent with advanced professional practice;
2. synthesise information from data and analyse the lifecycle of data within an organisation;
3. apply problem solving skills and advanced knowledge to implement data analysis solutions for real-world problems;
4. 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;
5. integrate theories and methods related to data science, statistics and software development by planning and executing a research-grounded industry project;
6. 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
7. demonstrate a sophisticated awareness of the ethical and legal issues that relate to the practice of data science.

All domestic students apply through the link below

International students apply direct to UNE through UNE International