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MSc Data Science for Politics and Policymaking

  • DeadlineStudy Details:

    12 months full time, 24 months part time

Course Description

The MSc in Data Science for Politics & Policymaking is designed to meet the growing demand for graduates with the ability to use big data to solve complex political and social problems. It’s perfectly suited to those looking for careers in political campaigns, think tanks, interest groups associated with shaping public policy and the civil service.

This Masters-level course equips you with the ability to design, commission, and implement projects that capture and analyse large quantities of online data from a diverse set of sources. It combines advanced training in social science research design and policy analysis with classes that enable you to understand the mechanics behind capturing and organising large amounts of data.

Entry Requirements

First- or upper second-class Honours degree, or overseas equivalent, in social science.

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Fees

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Student Destinations

The world is in the midst of a ‘big data’ revolution, with many companies and organisations seeking personnel who are able to interpret datasets that often appear as by-products of human-computer interaction.

Political campaigns, think tanks and interest groups associated with shaping public policy, and the civil service increasingly need graduates with the ability to design, commission, and implement projects that capture and analyse large swaths of online data from a diverse set of sources.

The expert training you will receive on this degree is in high demand as graduates of data analytics programmes often do not have the research design skills necessary to ensure successful project implementation while those trained in policy analysis lack the skills necessary to analyse the newer types of large, disconnected datasets that now are possible to mine. This course provides you with both skill sets.

Module Details

Core modules

Legal, Ethical & Professional Issues for the Information Society
Big Data Technologies
Database Fundamentals
Machine Learning for Data Analytics

And
Students with no quantitative experience:
Quantitative Methods 1
Students with quantitative methods experience:
Quantitative Methods 2
or
Qualitative Methods

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