The module is designed for students who have completed Year 1 and Year 2 of the Management Science BSc/MSci programme. In particular, it assumes that students...

The module is designed for students who have completed Year 1 and Year 2 of the Management Science BSc/MSci programme. In particular, it assumes that students have completed the modules in the Mathematics/Quantitative Thinking strand (MSIN0011, MSIN0015, MSIN0022), the modules in the Data Analytics strand (MSIN0010, MSIN0023, MSIN0025), as well as MSIN0014 Behavioural Science, MSIN0020 Strategy by Design and MSIN0024 Design.

Marketing professionals have long used data to measure campaigns and make marketing decisions. But with the advent of new channels and devices, marketers now have access to an unparalleled amount of data. Marketers need a more systematic way of capturing and analysing data, unearthing insights and using those insights to improve business outcomes.

Marketing Science revolves around understanding complex market dynamics and using various tools to predict outcomes and recommend actions. Marketing Scientists exhibit broader collaboration across the business, greater impact on customer engagement and a more pervasive culture of data-driven decision-making.

The aims of the Marketing Science module are:

To provide students with an understanding of key ideas and concepts in marketing.
 To expose students to the range of marketing problems that leading companies are addressing with scientific approaches and digital tools, and the results they are achieving.
 To provide students with practical experience of working with the range and types of data, models, and tools used in marketing science.

This module explores the issues that emerge when transforming complex, computationally generated data into a physical or virtual deliverable.

Advances in...

This module explores the issues that emerge when transforming complex, computationally generated data into a physical or virtual deliverable.

Advances in computational technology, such the development of general purpose computing using graphics processing units (GPU), allow personal computers to reach levels of performance that were previously only available at specialist supercomputing facilities. Combined with advances in computational fabrication, as well as in virtual, mixed and augmented reality, new possibilities are emerging for the creation and use of complex computed designs.

Of interest is the challenge of materialising the vast amount of detail and complexity we’re able to compute, pushing the capabilities of both physical fabrication and virtual representation.