Data Science and Artificial Intelligence (AI) in Practice is a Work Integrated Learning (WIL) course designed to develop the professional, technical, and workplace capabilities required of contemporary data science and AI practitioners. The course bridges academic learning and industry practice by engaging students in authentic, industry-informed tasks that reflect real-world data science and AI workflows. 

You will apply your developing knowledge of data analytics, machine learning, and data engineering in practical contexts, working with real or simulated industry datasets and problem scenarios. The course emphasises end-to-end project lifecycles, including problem framing, data acquisition and preparation, model development, evaluation, deployment considerations, and communication of insights to diverse stakeholders. 

A strong focus is placed on professional practice, including teamwork in multidisciplinary environments, stakeholder engagement, agile and collaborative workflows, version control, reproducibility, and documentation standards. You will also develop skills in communicating technical outcomes through reports, dashboards, visualisations, and presentations tailored to both technical and non-technical audiences. 

Ethical, legal, and governance considerations are embedded throughout the course. You will critically reflect on issues such as data privacy, bias and fairness in AI systems, responsible use of data, and professional accountability in organisational contexts. 

Through a combination of industry case studies, project-based learning, and reflective activities, you will build confidence in applying these skills in workplace settings. The course prepares graduates to transition effectively into professional roles in data science and AI, aligning with industry expectations and AQF Level 9 outcomes for applied knowledge, autonomy, and professional responsibility.