Data Science brings together key ideas from fields such as computer science (algorithms, representation, visualization, application development), statistics (modelling, analysis, prediction), design (information design, interaction design), psychology and cognitive science (language and perception), and the humanities and social sciences (storytelling and narrative, social learning) among others. At it’s core Data Science is about developing the infrastructure and processes for dealing with data at scale, recognising and understanding patterns within large, diverse datasets, generating predictions based on these patterns, and creating revealing visualizations and crafting compelling narratives with and about data. Data science emphasises the role of data – large and small, real-time and archival, noisy and uncertain – in large-scale problem solving, but it also speaks to the disruptive role that data-driven methods are playing in transforming a host of traditional disciplines (from the humanities and social sciences to life sciences, business, and law) and virtually all aspects of modern society (from business and commerce, to healthcare and government).
This module will equip students with a full suite of data science tools and enable them to develop data science solutions to answer questions and solve problems. Students will learn how to frame questions as data science questions, data preparation and manipulation techniques, machine learning methods, information visualization approaches and how to communicate with data. They will also develop a number of end-to-end data science projects.