15 Credits ACADEMIC YEAR


Pre-requisites: none

none


Aims/Description: This module will introduce machine learning, cluster analysis, social network analysis, textual analysis and data visualisation. The course will emphasise methods that can be applied to real-world applications to spatial and time series data. Employable skills include techniques for analysing large complex datasets in non-standard ways. A programme of lectures, guided practical classes and independent study will help develop a set of hands-on practical skills useful for social science applications. Students will undertake a small secondary data analysis project for assessment.

Restrictions on availability: Yes this course is restricted to students from the Universities of Sheffield, Liverpool, Leeds and Manchester enrolled with the CDT Data Analytics and Society.

Staff Contact: Amy Clare
Teaching Methods: Lectures, Tutorials, Problem solving, Independent Study
Assessment: Course work

Information on the department responsible for this unit (Methods Institute):

Teaching timetable

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NOTE
The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

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Western Bank, Sheffield, S10 2TN, UK