ETW3483 · Applied analytics

Overview

Understanding data for insights is an essential prerequisite for driving competitive advantage in this digital era. This unit will cover key concepts and skills in open data management, advanced visualization, statistical machine learning, and the analytical life cycle of an analytical research project. You will learn essential data and statistical methods to leverage data as a strategic asset for better decisions and recommendations. By applying analytics in a research project, you will be able to use open data responsibly, visualize trends and patterns, interpret and predict outcomes, and finally, communicate results and insights to stakeholders in the global environment.

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. distinguish a realistic global challenge that can be addressed using open data
2. use relevant and credible open data to conduct analytical research responsibly
3. evaluate trends and patterns for effective visualization and statistical analysis
4. produce explainable models to communicate result-driven insights for global stakeholders.

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.