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BSc Computer Science (Cyber Security)

Royal Holloway, University of London

Institution
Royal Holloway, University of London
Level
undergraduate
Subject
Computer Science (Cyber Security)
Duration
3 years
UCAS code
G407
Typical offer
A-level AAB, IB 34

Entry requirements

A level: AAB-ABB (Required subjects: Computer Science or Mathematics or Physics. GCSE Mathematics at grade 6 (B) GCSE English Language at grade 4 (C) For students taking the BTEC Extended Diploma please click here to see the specific modules you must take in order to meet the entry requirements for this course.) IB: 6,6,5 at Higher level or 34 points overall. Including either Physics, Computer Science or 5 HL Maths: Analysis & Approaches/6 HL Maths: Applications & Interpretation/6 SL Maths: Analysis & Approaches

About this course

BSc in Computer Science and Software Engineering. Core topics include Programming, Computer Architecture, Embedded Systems, Control Systems, Statistics, and Artificial Intelligence & Machine Learning. The programme offers a cybersecurity pathway with modules on cryptography, network security, and critical infrastructure security. The BSc is certified by the National Cyber Security Centre (NCSC).

Modules

  • Object Oriented Programming I
  • Object Oriented Programming II
  • Programming laboratory
  • Internet Services
  • Mathematical Structures
  • Machine Fundamentals
  • Mathematical Methods for Computer Science
  • Software Design
  • Academic Integrity
  • Software Engineering
  • Team Project
  • Operating Systems
  • Databases
  • Algorithms and Complexity
  • Introduction to Information Security
  • Computer and Network Security
  • Symbolic Artificial Intelligence
  • Multi-dimensional Data Processing
  • Security Management
  • Applications of Cryptography
  • Full Unit Project (Information Security)
  • Computational Finance
  • Intelligent Agents and Multi-agent Systems
  • Machine Learning
  • Critical Infrastructure Security
  • Digital Forensics
  • Smart Cards, RFIDs and Embedded Systems Security
  • IT Project Management
  • Software Language Engineering
  • Compilers and Code Generation
  • Computational Optimisation
  • Functional Programming and Applications
  • Deep Learning
  • Software Verification
  • Advanced Algorithms & Complexity