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 (e.g. engineering or computer science) or social science subjects (e.g. psychology, criminology or geography). Alternatively candidates may qualify for entry if they can offer five or more years of relevant professional experience (for example in the police service, or as a crime prevention worker).
If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.
The English language level for this programme is: Good.
Further information can be found on our English language requirements page.
Months of entry
This programme provides students with a thorough understanding of how science and scientifically-based techniques can deliver immediate and sustainable reductions in crime. The programme focuses on how to apply science better to understand crime problems, develop investigative strategies for preventing them and increase the probability of detecting and arresting offenders.
UCL Security and Crime Science is a world first, devoted specifically to reducing crime through teaching, research, public policy analysis and by the dissemination of evidence-based information on crime reduction.
Crime science is supported by the police, forensic psychologists, applied criminologists, economists, architects, statisticians and geographers, and has been strongly endorsed by the government.
This multidisciplinary programme draws on expertise in psychology, geography, criminology, philosophy and a range of forensic sciences. Our graduate students come from varied backgrounds; many are practitioners and are encouraged to contribute their experience in and out of the classroom.
Fees and funding
Fee Please see UCL website for full information about fees and costs for this programme.
Qualification and course duration
The programme is delivered through lectures, seminars, tutorials, projects, laboratory classes, and practical exercises. Practical work will involve the analysis and interpretation of datasets, and the development of new ideas for solving problems. Assessment is through laboratory and project reports, unseen written examinations, coursework and presentations.
Course contact details
- +44 (0)20 3370 1214