Unsupervised learning for business

Unsupervised learning for business is a specialised field within machine learning that focuses on extracting valuable insights and knowledge from unlabelled data in a business context. Unlike supervised learning, which relies on labelled data for training, unsupervised learning algorithms work with unstructured or unlabelled data to discover patterns, structures, or relationships that may not be immediately apparent. This unit explores various techniques and methodologies used in unsupervised learning to address specific business challenges and opportunities. It delves into applying these techniques to large and complex datasets, enabling businesses to make data-driven decisions and gain a competitive advantage.

Active learning - This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.

Problem-based learning - This unit includes problem-based learning approaches, where you engage in research, integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems.

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.