ETW2500 · Unsupervised learning for business

Overview

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.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. apply various pre-modeling, descriptive and unsupervised learning techniques to different business scenarios
2. critically analyse complex business problems to unsupervised learning using various analytical software
3. effectively communicate the results of unsupervised learning techniques for a business problem
4. demonstrate the use of various technological skills related to analytics and research for lifelong learning.

Workload

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.

Student experience, not official rules. Nothing here changes what the Handbook says.