Data is ubiquitous in modern society. It is used to monitor the economy, inform business decisions, understand how the environment is changing, and communicate public health messages. Data science is a booming field that harnesses raw data and turns it into actionable knowledge. Data Scientists develop and employ tools to collect, understand and communicate data and its meaning. They are able to identify trends, understand demographics and inform interventions. They are able to work across disciplines, from science to business, health, media and politics. But data can also be misused, and a professional Data Scientist will understand the ethical demands of responsible use of data. This hands-on unit provides practical experience, using the programming language Python, for solving real-world data science problems, from acquiring data from public sources, to understanding the data through analysis and modelling, to visualising and presenting the results.

Students are able to (1) understand and implement the stages in the data science lifecycle, from data acquisition and cleaning through to analysis, modelling and visualisation; (2) independently research, solve and communicate results for real-world data science problems from across a range of disciplines; (3) demonstrate a command of computational structures and operations, and discuss the relevant efficiency and storage implications of alternative solutions; (4) utilise appropriate encoding and visualisation methods for different types of data, including categorical, numerical and time-series data; (5) understand the power of data used well or used poorly, and critically assess the way data is used and presented in business, science, the media and the wider community; and (6) recognise and discuss the ethical responsibilities of a data scientist.