Program Overview

Crime Intelligence and Data Analytics MSc

Overview

The work boundaries of traditional police intelligence analysts and digital forensic investigators are becoming blurred. Analysts now need to be cyber aware and understand how communication records and web search histories can be extracted and analysed.

This course covers these areas and the theories to help understand the causes of crime and the prevention measures to stabilise and reverse these trends. You develop the skills to work effectively with large datasets, allowing you to make more informed decisions in relation to criminal investigations. Key features include writing code to quickly clean up data and packaging it so it’s suitable for analysis and visualisation. You explore strategies employed in forensic investigation and develop your own area of interest in a research project where you maximise your skillsets, from academic writing to data analytics.

Course Structure

Core Modules

• Advanced Research Project: This is your opportunity to undertake a major independent practical research project in your discipline. You work independently and to a level recognised to be at the forefront of the discipline.
• Coding for Intelligence Analysts: You learn basic coding with teaching geared to providing support to first-time coders. Coding is primarily about data analysis, cleaning, and merging data before it’s visualised in charts and tables.
• Crime Science: Theories, Principles and Intelligence Sources: You study crime theories and principles, such as rational choice, routine activity, problem profile models packaged up in environmental criminology.
• Criminal Justice and the Forensic Practitioner: Forensic practitioners are called upon to act in some of society’s most challenging situations (in the crime scene, custody block and mortuary) to do crucial work in evidence recovery, analysis, and interpretation.
• Cyber Security and Digital Investigation: Understanding how computers, tablets, mobile communications, and the internet of things store information about our activity is a fundamental aspect of this module.
• Forensic Investigative Strategy: You develop an understanding of the principles associated with crime scene science and its relationship with forensic analysis and the legal process.
• Managing and Mapping GIS Data: Spatially-explicit data is used across industries such as logistics, land planning, crime pattern analysis and behavioural studies.

How You Learn

You usually complete three hours of taught content a week for each module. There are three modules each semester so this equates to nine hours or more of taught content a week. You learn through lectures, seminars and practical IT or laboratory sessions. You also have independent study as well as tasks and technical problems to solve each week.

How You Are Assessed

You are assessed through technical reports and practical examinations, and provided with formative feedback before final submissions.

Entry Requirements

You must have a 2:2 degree or higher in a suitable undergraduate subject that contained strong research methods content such as social science, humanities, law, science, engineering.

Employability

Career Opportunities

You could expect to apply for roles including crime intelligence researcher, crime intelligence analyst, business intelligence analyst, data analyst, data modeller and researcher. Opportunities exist within the business sector, law enforcement, probation service and local government.

Information for International Applicants

Qualifications

International applicants - find out what qualifications you need by selecting your country below.

Fees

Full-time

• Fee for UK applicants: £8,365 a year
• Fee for international applicants: £17,000 a year

Part-time

• Fee for UK applicants: £930 for each 20 credits

Length and Attendance

Full-time

• Length: September enrolment: 1 year, January enrolment: 16 months, including a summer break
• Start date: January or September
• Semester dates

Part-time

• Length: September enrolment: 2 years, including a summer break
• Attendance: 2 days a week
• Start date: September
• Semester dates