Summary

Genomics is rapidly becoming an essential component of medical practice across a range of fields. Cancer clinicians use genomics to profile patients...

Summary

The Research Project is the largest single component of the MSc, contributing one third of the credits. This is a key component that distinguishes the...

SOCIAL LICENSING|STAKEHOLDER ENGAGEMENT|STAKEHOLDER NETWORKS|SOCIAL LICENCE TO OPERATE|CRISIS MA

Aims:

One of the key factors in the success of any project is managing stakeholders’ demands and expectations. Over the course of this module students...

MIXED MODE|DEVELOPING PEDAGOGY|CPD|EDUCATION PRACTICE|MASTER OF TEACHING

The Leading Learning (LL) module is aimed at experienced teachers, whose expertise provides a practical foundation for, and informs a critical analysis of, the...

Computer Science|Information and Data Science|Interaction Design|Web development

This module investigates the technical architecture underlying the Web, its subsequent evolution to deal with problems of scale and real-time interaction, the...

This module investigates the technical architecture underlying the Web, its subsequent evolution to deal with problems of scale and real-time interaction, the research that has informed its development and expanding to the future of the platform beyond the classic use of sharing and disseminating data. The student will learn how to create website to interact with devices and create interactive visualisations to analyse various datasets. Students will explore the different frameworks and their use within the browser.


Aim: To give the student an exposure and understanding of what makes a good web application, and developing a skill set to design and build a web interfaces and applications that interact with the physical as well as the digital interfaces.

The module aims to introduce students to the mathematical modelling of urban systems within the framework of complexity science. From the wide range of...

The module aims to introduce students to the mathematical modelling of urban systems within the framework of complexity science. From the wide range of modelling techniques, only two will be introduced: spatial interaction models and network science. These are widely used to model emergent patterns from the local interactions. In particular, we will look at modelling flows between areas, considering the characteristics at the different locations, and their spatial distribution. We will also learn to encode different types of interactions, the role of the different agents (people or places for example), and how the global structure of the system affects the different processes taking place.

The skills learnt in this course can be applied to a wide range of systems. During the course we will look at transport systems and the modelling of flows related to commuting patterns. We will assess the role of transport nodes using centrality measures, and the resilience of the system using global measures. The framework is exemplified on social systems as well, where techniques such as community detection are more natural.

Prerequisites: basic knowledge of Python, or a good knowledge of another programming language. The student should be able to understand and modify the codes given in the course in Python. Basic linear algebra will be reviewed, but it is strongly advised to review matrices and vectors before the start of the course.