(Award available for year: Master of Science)
Master of Science
Learning Outcomes:
On completion of the year/programme students should have provided evidence of being able to:
-demonstrate in-depth, specialist knowledge and mastery of techniques relevant to applying data science in the urban and/or transportation contexts;
-develop a detailed understanding, and creative application, of diverse concepts, information, and techniques at the forefront of urban studies and urban planning;
-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;
-take a proactive and self-reflective role in working and to develop professional relationships with others in academic and industrial contexts;
-formulate ideas and hypotheses and to develop, implement, and execute plans by which to evaluate these;
-critically and creatively 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:
-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;
-identify, select, and critically evaluate datasets for analysis of urban and/or transportation phenomena;
-The academic and work-ready 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, ensuring continual professional development.
Assessment:
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 draw on a range of perspectives on an area of study, evaluate and critique received opinion, and apply breadth and/or depth of knowledge to a complex challenge in a specialist area;
-demonstrating creativity in the application of data science methods towards the understanding of urban and/or transportation challenges;
-making reasoned judgements whilst understanding the limitations on inferences made in the absence of complete data.
Errors, omissions, failed links etc should be notified to the Catalogue Team