Security and Data Science MSc

Program Overview

The MSc Security and Data Science program equips students with both data science skills and a deep understanding of the security-threat landscape in the context of emerging technologies like AI. Graduates possess a dual specialization that prepares them for roles in security, defense, and law enforcement, where they can analyze security threats, develop security policies, and apply data science techniques to improve security. The program is delivered by the Centre for Computational Social Science, which specializes in providing quantitative and computational social research training to individuals from diverse backgrounds.

Program Outline

Degree Overview:

The MSc Security and Data Science program offers a unique blend of in-depth knowledge and understanding of security issues related to emerging technologies like artificial intelligence (AI) and data. It aims to equip students with practical experience in working with data and developing associated skills that are highly sought after in the security, defense, and law enforcement sectors. The program is designed for individuals with no prior experience in data or computer coding, as it provides all necessary skills at a suitable level for beginners. Students will explore areas such as:

• How law enforcement utilizes data for predictive policing.
• The use of generative AI by extremist groups.
• The role of AI in developing cybersecurity systems.
• The application of AI in intelligence gathering and military decision-making.
The program emphasizes learning to code in Python and its application in data science methods, a highly employable and transferable skillset both within and beyond the security, defense, and law enforcement sectors. Delivered by the Centre for Computational Social Science (C2S2), the program specializes in providing quantitative and computational social research training to individuals from diverse academic and professional backgrounds, particularly those with no prior experience. Graduates of this program will possess a dual specialization in data science skills and a strong understanding of the security-threat landscape, enabling them to adapt to the novel opportunities and threats posed by emerging technologies, particularly data and AI. This dual specialization prepares them for roles in organizations such as:
• Security services
• National Crimes Agency
• Europol
• Interpol
• Specialist policing units
• Business intelligence and analytics
• Data journalism
• Social research
• Specialized government departments focused on security, defense, and law enforcement domains.

Outline:

The program's content is structured to develop students' knowledge of the security-threat landscape in the context of contemporary emerging technologies, particularly the roles of data and artificial intelligence (AI). Students will learn about the nature of these changes and how both malicious actors and security, defense, and law enforcement organizations are adapting to the threats and opportunities posed by these technologies. The program introduces students to the interdisciplinary field of data science, equipping them with the ability to gain actionable insights from data. This is achieved without assuming prior knowledge or experience in working with data or computing, providing students with the specific practical data skills that security, defense, and law enforcement organizations increasingly seek in prospective employees. The program ensures that students have the domain-specific knowledge and technical skills necessary to understand the opportunities and threats posed by technological developments within both the current and future security-threat landscape, positioning them for successful careers in these sectors.

Compulsory Modules:

• The Security-Threat Landscape in the Age of Data and AI: This module explores the evolving security-threat landscape in light of emerging technologies, particularly data and AI.
It examines how these technologies are being used by both malicious actors and security, defense, and law enforcement organizations. It focuses on applying data science methods to security-related problems. Students will learn how to use Python to perform data analysis, machine learning, and visualization.

Optional Modules:

• Global Security: This module examines global security challenges, including terrorism, cybercrime, and organized crime.
It explores the role of international organizations in addressing these challenges.
• Machine Learning for Social Data Science: This module introduces students to machine learning techniques and their application to social data science.
It covers topics such as supervised learning, unsupervised learning, and deep learning. It covers topics such as network security, cryptography, and incident response.
• Intelligence Analysis: This module explores the methods and techniques used in intelligence analysis.
It covers topics such as open-source intelligence, human intelligence, and signals intelligence.

Assessment:

The program's assessment methods may vary depending on the specific modules. However, common assessment methods include:

• Essays: Students will be required to write essays on various topics related to security, data science, and emerging technologies.
• Presentations: Students will present their research findings and analysis to their peers and instructors.
• Projects: Students will undertake individual or group projects that involve applying their knowledge and skills to real-world security problems.

Teaching:

The program's teaching methods typically involve a combination of:

• Lectures: Lectures provide students with a foundational understanding of key concepts and theories.
• Seminars: Seminars offer opportunities for students to engage in discussions, share their perspectives, and ask questions.
• Group Work: Group work encourages collaboration and teamwork, allowing students to learn from each other and develop their communication skills.
• Practical Sessions: Practical sessions provide hands-on experience with data analysis tools and techniques.
The program is delivered by experienced faculty members who are experts in their respective fields. They bring a wealth of knowledge and practical experience to the classroom, ensuring that students receive a high-quality education.

Careers:

Graduates of the MSc Security and Data Science program are highly sought after by employers in the security, defense, and law enforcement sectors. The program's unique blend of data science skills and security knowledge prepares graduates for a wide range of career opportunities, including:

• Security Analyst: Analyze security threats and vulnerabilities, develop security policies and procedures, and implement security controls.
• Intelligence Analyst: Collect, analyze, and interpret intelligence information to support decision-making in security, defense, and law enforcement organizations.
• Cybersecurity Analyst: Protect computer systems and networks from cyberattacks, investigate security incidents, and implement security measures.
• Forensic Analyst: Investigate digital evidence to support criminal investigations and legal proceedings.

Other:

The program is delivered by the highly successful Centre for Computational Social Science (C2S2), which specializes in providing quantitative and computational social research training to people from all academic and professional backgrounds, especially those with no prior experience. The program emphasizes the practical skills associated with working with data using a range of programming and data analytics software, including Python. The program offers a variety of additional training as part of the Centre for Computational Social Science (C2S2), including:

• Applied Data Analysis workshops: These workshops provide additional support to students interested in Quantitative Methods for the Social Sciences.
They aim to raise interest in Applied Data Analysis among both undergraduates and postgraduates and embed quantitative literacy in wider University practice.
• The Centre for Computational Social Science seminar series: This is a long-running successful annual postgraduate conference that brings together researchers from across all humanities and social science disciplines.

2024/25 entry UK fees per year: £12,000 full-time; £6,000 part-time International fees per year: £24,300 full-time; £12,150 part-time