Bachelor of Science (Hons) Cyber Security and Artificial Intelligence

This module provides students with an advanced understanding of how artificial intelligence, machine learning, and data analytics can be applied to support evidence-based decision-making in organisational, business, and technological contexts. Students will examine techniques for collecting, preparing, analysing, and interpreting data to generate actionable insights. The curriculum explores predictive modelling, decision intelligence frameworks, data visualisation, and AI-supported decision systems, with emphasis on practical application, strategic decision support, and clear communication of insights to technical and non-technical stakeholders.

This module develops students’ understanding of network security, cloud security, and the application of artificial intelligence to strengthen modern digital infrastructure. Students will examine network architectures, cloud service models, identity and access management, encryption, monitoring, intrusion detection, and security controls across cloud and hybrid environments. The curriculum also explores how AI can automate threat detection, identify anomalies, support predictive security, and improve cyber defence capabilities.

This module introduces students to the principles and applications of cryptography, blockchain technologies, and secure system design. Students will examine symmetric and asymmetric encryption, hashing, digital signatures, key management, authentication mechanisms, blockchain architecture, consensus mechanisms, smart contracts, distributed ledgers, and their implications for secure digital transactions and decentralised systems. The module emphasises critical evaluation of strengths, limitations, vulnerabilities and governance issues in real-world contexts.

This module examines how artificial intelligence can be applied to cyber threat intelligence, malware analysis, and proactive cyber defence. Students will explore contemporary cyber threats, attack vectors, malware behaviours, and threat intelligence frameworks. The curriculum introduces machine learning and analytical techniques used to classify malware, detect anomalies, identify malicious patterns, and support incident response, while also considering false positives, adversarial attacks, explainability, ethics and operational risk.

This capstone module provides students with the opportunity to undertake a substantial independent project that integrates knowledge and skills developed across the Bachelor of Science programme. Students will identify a relevant real-world, workplace, industry-informed or professionally situated problem; engage with relevant stakeholder, user, employer, practitioner or industry evidence; conduct an appropriate academic and professional literature or contextual review; design and implement a solution or investigation; and evaluate its effectiveness. Depending on the pathway, the project may focus on cyber security, computing, artificial intelligence, data science, intelligent systems, secure systems or human-centred technology. The module emphasises independent learning, technical depth, critical thinking, innovation, responsible practice, industry relevance and professional communication.