15 Credits SPRING

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: TAYLOR MARK R
Teaching Methods: Lectures, Laboratory work, Independent Study
Assessment: Course work

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

Teaching timetable


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 Individual modules are occasionally updated or withdrawn.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.

URLs used in these pages are subject to year-on-year change. For this reason we recommend that you do not bookmark these pages or set them as favourites.

Teaching methods and assessment displayed on this page are indicative for 2021-22. Students will be informed by the academic department of any changes made necessary by the ongoing pandemic.

Western Bank, Sheffield, S10 2TN, UK