This module introduces students to the fundamental techniques, concepts and contemporary discussions across the broad field of data science. With data and data related artefacts becoming ubiquitous in all aspects of social life, data science gains access to new sources of data, is taken up across an expanding range of research fields and disciplines, and increasingly engages with societal challenges. The module provides an advanced introduction to the theoretical and scientific frameworks of data science, and to the fundamental techniques for working with data using appropriate procedures, algorithms and visualisation. Students learn how to critically approach data and data-driven artefacts, and engage with and critically reflect on contemporary discussions around the practice of data science, its compatibility with different analytics frameworks and disciplinary, and its relation to on-going digital transformations of society. As well as lectures discussing the theoretical, scientific and ethical frameworks of data science, the module features coding labs and workshops that expose students to the practice of working effectively with data, algorithms, and analytical techniques, as well as providing a platform for reflective and critical discussions on data science practices, resulting data artefacts and how they can be interpreted, actioned and influence society.
2020/21
Course image IM903:Complexity in the Social Sciences
2020/21
Course image IM913:Spatial Methods and Practice in Urban Science
2020/21
Course image IM923:User Interface Cultures: Design, Method and Critique
2020/21
Course image IM924:Philosophy of Social Science Research
2020/21
Course image IM925:Foundations in Qualitative Research
2020/21
Course image IM926:Research Design, Practice and Ethics
2020/21
Course image IM931:Interdisciplinary Approaches to Machine Learning
2020/21
Course image IM939:Data Science Across Disciplines: Principles, Practice and Critique
2020/21
Course image QS906:Big Data Research: Hype or Revolution?
2020/21