COURSE CURRICULUM

The Master of Predictive Analytics with a major in Data Science at Curtin University requires students to complete 400 credits to graduate, with most units carrying 25 credits each unless stated otherwise. The course is structured across four trimesters and focuses on advanced data science, predictive analytics, machine learning, and research skills. In the first trimester, students build foundational knowledge through subjects such as Data Management, Decision Methods and Predictive Analytics, Fundamentals of Programming, and STEM Research Methodologies. These units help students develop programming, analytical thinking, research, and data handling skills essential for modern data science careers. In the second trimester, students study specialised topics including Fundamental Concepts of Data Security, Data Structures and Algorithms, Data Mining, and Business Quantitative Techniques. These subjects focus on data analysis, information security, computational methods, and quantitative business problem-solving. In the third trimester, students gain advanced knowledge through units such as Explainable Approaches to Machine Learning and New Product Development, while elective units allow students to explore additional areas of interest and specialisation. The final trimester includes further elective studies and a major Predictive Analytics Project worth 50 credits, enabling students to apply advanced analytical and research skills to real-world data science challenges. The program prepares graduates for careers in data science, predictive analytics, business intelligence, and machine learning across diverse industries.