Data challenges 4

This is the fourth in a series of Data Challenges units which builds on industry-relevant data science case studies explored during the first three semesters of the course. Team-based learning is used to further develop and apply the suite of analytical skills required to discover the underlying answers to questions raised by large and complex sets of data. A broad range of problems will be presented from both STEM and humanities disciplines, including both academic and industry focused examples, and guest lectures will give students an insight into real problems faced by experts in the field. Students will continue to discuss the technical and ethical elements of data, with a focus on data collection methods, scientific thinking, and issues surrounding privacy and to communicate project outcomes through a combination of written, oral and multimedia visualisations. You will also work in teams to apply the key principles, tools and techniques of data science to complex industry problems, and develop their capacity to communicate their analysis and ethical considerations to a range of potential stakeholders.