Case Studies in Data Science 1 teaches you the end-to-end process of approaching a data science problem, including how to pose a data science question for a given domain and problem; the application of design thinking to structure an approach; how to implement a data science task using teamwork and agile methodology; how to evaluate results and present them to stakeholders. All techniques will be presented in the context of ethical practice, data security, privacy and governance, and legal and regulatory constraints.

Various case study options will be offered involving different business domains (e.g., finance, health, transport, etc) and/or different types of data (e.g., structured, text, large-scale).

This is a designated WIL course. Your knowledge and skills will be applied and assessed in an environment where feedback from data scientists working in industry is integral to your experience. Any or all of these aspects of a WIL experience may be in a simulated workplace environment.