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MSc Urban Data Science and Analytics

Year 1

(Award available for year: Master of Science)

Learning outcomes

On completion of the year/programme students should have provided evidence of being able to:

to demonstrate in-depth, specialist knowledge and mastery of techniques relevant to applying data science in the urban and/or transportation contexts;

to demonstrate a sophisticated understanding of concepts, information and techniques at the forefront of urban studies and urban planning;

to demonstrate creativity in the practice of urban data science, through integration of diverse methods, tools, and thinking towards understanding complex urban phenomena;

to apply data science methods to observed urban policy challenges, including understanding the process of policy decision-making, working with external stakeholders and citizens where appropriate;

to exhibit mastery in the exercise of generic and subject-specific intellectual abilities;

to take a proactive and self-reflective role in working and to develop professional relationships with others;

proactively to formulate ideas and hypotheses and to develop, implement and execute plans by which to evaluate these;

critically and creatively to evaluate current issues, research and advanced scholarship in the discipline.

Transferable (key) skills

Masters (taught), Postgraduate Diploma and Postgraduate Certificate students will have had the opportunity to acquire the following abilities, as defined in the modules specified for the programme:

to practice data science within the urban and/or transportation context, through creative use of modern programming languages and datasets, to shed light on urban and/or transportation phenomena.

ability to identify, select, and evaluate datasets for analysis of urban and/or transportation phenomena.

the skills necessary to undertake a higher research degree and/or for employment in a higher capacity in industry or area of professional practice;

evaluating their own achievement and that of others;

self direction and effective decision making in complex and unpredictable situations;

independent learning and the ability to work in a way which ensures continuing professional development;

critically to engage in the development of professional/disciplinary boundaries and norms.


Achievement for the degree of Master (taught programme) will be assessed by a variety of methods in accordance with the learning outcomes of the modules specified for the year/programme and will include:

evidencing an ability to conduct independent in-depth enquiry within the discipline;

demonstrating the ability to apply breadth and/or depth of knowledge to a complex specialist area;

demonstrating creativity in the application of data science methods towards the understanding of urban and/or transportation challenges;

drawing on a range of perspectives on an area of study;

evaluating and criticising received opinion;

making reasoned judgements whilst understanding the limitations on judgements made in the absence of complete data.


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