The Master of Predictive Analytics addresses the growing demand for data scientists who have the right blend of technical and analytical skills to meet the challenge of big data analytics. It is currently the only master degree course in predictive analytics in Australia. It is a multidisciplinary degree, in which you can choose from four majors to learn about specific application domains. It introduces advanced skills in data management, mining and visualisation, decision methods and predictive analytics, with a focus on their applications to different disciplines, such as engineering, networking, business and finance. You will have opportunities to work on industry-sponsored projects, and participate in Curtin partnerships through Innovation Central Perth and the Curtin Institute for Data Science.The Finance and Investment Analytics Major provides students with the ability to develop predictive models for purposes of formulating appropriate investment strategies. The Major focuses on the nexus between data analytics, economic modelling and the operations of financial markets. While the emergence of "big data" means a great amount of information are available to investors and regulators, their usefulness remains elusive. The main issue is that the extraction of this information from such large scale data and their translation to useful insight for decision making requires seamless integration of computer programming, statistics, econometrics and a thorough understanding of the operations of our economies and financial markets. This course is designed to fill this gap by providing students with a broad scope of skills covering these diverse areas in an integrated manner. After completing the first year of Master of Predictive Analytics or Graduate Diploma in Predictive Analytics, students would possess broad skills in data security, data management and predictive analytics. In this one year major, the first semester will be dedicated to the understanding of financial market operations, investment strategies, economic and econometric modelling and the roles that data analytics plays in this area. In the second semester, students will dive deeper into the connection between machine learning and modern econometrics. There will also be an opportunity for students to sharpen their skills and understanding by completing an industry-inspired project.