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MSc Crime Science with Data Science

  • DeadlineStudy Details: 1 year - 5 years

Masters Degree Description

This multidisciplinary Crime Science with Data Science MSc combines crime science methodology with the latest data science approaches. During this programme, you will find practical applications for the latest data science tools and techniques and harness a range of groundbreaking new technologies to help fight crime.

Entry Requirements

Normally a minimum of a second-class Bachelor's degree in a relevant discipline from a UK university or an overseas qualification of an equivalent standard. Relevant disciplines include science subjects and those with a significant component of statistics, mathematics or quantitative methods. For example engineering, computer science or psychology. Alternatively, candidates may qualify for entry if they can offer five or more years of relevant professional experience (for example as a data scientist, data engineer or intelligence analyst).

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Fees

For fees and funding options, please visit website to find out more.

Student Destinations

Our graduates are fully equipped for exciting careers on the frontlines of crime science, in areas such as intelligence and crime prevention analysis.

Module Details

Compulsory modules

  • Preventing Crimes
  • Foundations of Security and Crime Science
  • Security and Crime Science Dissertation
  • Applied Data Science
  • Simulation for research
  • Understanding Multivariate Modelling and Causal Inference
  • Crime Mapping and Spatial Analysis
  • Perspectives on Organised Crime
  • Investigation and Detection
  • Intelligence Gathering and Analysis
  • Risk and Contingency Planning
  • Introduction to Cybersecurity
  • Qualitative Research Methods
  • Cybercrime
  • Horizon Scanning and the Changing Nature of Crime
  • Machine Learning for Data Science
  • Online Extremism and Hate Crime
  • Assessing Extremism Risk
  • Human trafficking, smuggling and exploitation

Optional modules

  • Crime Mapping and Spatial Analysis
  • Perspectives on Organised Crime
  • Investigation and Detection
  • Intelligence Gathering and Analysis
  • Risk and Contingency Planning
  • Introduction to Cybersecurity
  • Qualitative Research Methods
  • Cybercrime
  • Horizon Scanning and the Changing Nature of Crime
  • Machine Learning for Data Science
  • Online Extremism and Hate Crime
  • Assessing Extremism Risk
  • Human trafficking, smuggling and exploitation
  • reasonable adjustments
  • Student Support and Wellbeing Services
  • UCL Student Support and Wellbeing Services
  • AccessAble
  • UCL Student Support and Wellbeing Services.

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