students will learn how to use data to boost athlete performance and wellbeing. students will get hands-on experience with industry-standard technologies, such as wearable sensors (catapult gps and imeasureu accelerometers), computer vision and video annotation software (keemotion and sportscode), and athlete management systems.

students can see where their new skills can take them. courses cover talent id, athlete management, performance and injury modelling, and broadcasting and fan engagement. students will develop an intricate understanding of cutting-edge machine learning techniques and use advanced analytics tools, including r, python and sql – all required for a successful career in sport analytics and data science.

in the second year, students will have the opportunity to complete a practical learning project. they could work under the supervision of an industry expert or academic and hone their data analysis skills in a real industry setting. previous students have completed projects with tennis australia, afl victoria, champion data, and carlton and st kilda football clubs.

students will learn:

• sport analytics methods
  • understand the basic practices for capturing, handling, cleaning and processing data generated from sport.
• generating insights from data
  • learn how to use data to develop insights into talent identification, athlete management, injury management and fan engagement.
• machine learning techniques
  • understand and use data-programmed machines to detect patterns and predict future sporting events.
• data visualisations
  
  • learn to select and use analytical tools and visualisations to clearly communicate outcomes and findings.