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MSc Data Science and Public Policy (Political Sciences)

  • DeadlineStudy Details:

    MSc 1 year full-time

Masters Degree Description

The size and complexity of digital information now available has the potential to improve how we understand, design, implement and evaluate effective public policy. Co-taught by UCL Economics and Political Science, this course will equip you as a policymaker to translate this wealth of information into useful insight, using cutting-edge data-science methods, rich technical skills, and detailed knowledge about economic and political processes.

Entry Requirements

A minimum of an upper second-class Bachelor's degree from a UK university; or an overseas qualification of an equivalent standard. All applicants must provide evidence of successfully completing at least one advanced module in quantitative methods, statistics, data science or econometrics during their Bachelor's degree.

Relevant practical or work experience in a related field may also be taken into account. For example, this might include: i) at least two years of experience working in a public sector organisation, a think tank, an international-governmental organisation, or in a public-policy consultancy role; or ii) at least two years of experience working in a data-science role.

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Fees

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Student Destinations

The programme is designed to teach you the knowledge and skills required to provide insight into important questions in public policy using advanced statistical methods. A series of in-depth substantive modules, delivered by economists and political scientists, will provide you with the analytical tools to think deeply about important questions in policymaking. The methodological training will enable you to understand and, crucially, apply cutting-edge quantitative methods to real-world problems. Our research-based curriculum promotes a variety of research skills, which will enable you to understand, and contribute to, quantitative analyses of public policy.

Module Details

Compulsory modules

  •  Statistical Learning for Public Policy
  •  Data, Evidence and Public Policy
  •  Statistical Programming for Social Data Science
  •  The Politics of Public Policy
  •  Dissertation

Optional modules

  •  Data Science Theory
  •  Machine Learning in Economics
  •  Causal Inference
  •  Quantitative Text Analysis for Social Science
  •  International Political Economy
  •  Public Management: Theories and Innovations
  •  Terrorism
  •  Making Policy Work
  •  Policy Implementation
  •  Law and Regulation I
  •  International Trade Policy
  •  The Political Economy of Development

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