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    Cybersecurity and Artificial Intelligence

    Department of Computer Science, Faculty of Engineering

    Receive a grounding in the fundamentals of cybersecurity and artificial intelligence. We teach you how to apply what you learn in business and industry, anywhere in the world.
    Computer Science postgraduates using 3D computer graphics

    Course description

    This course combines two disciplines: cybersecurity and artificial intelligence (AI). Cybersecurity is one of the most pressing problems of our time and artificial intelligence has made great advances in recent years. Skills in both areas are very much in demand.

    You will receive a grounding in the fundamentals of cybersecurity and AI. There are taught modules in each of these disciplines and you’ll carry out a project that addresses a research problem (or problems) at the interface of the two.

    Applying for this course

    We use a staged admissions process to assess applications for this course. You'll still apply for this course in the usual way, using our Postgraduate Online Application Form.


    This course is accredited by the British Computer Society (BCS). The course partially meets the requirements for Chartered Information Technology Professional (CITP) and partially meets the requirements for Chartered Engineer (CEng). This degree is certified by the National Cyber Security Centre (NCSC).


    A selection of modules is available each year - some examples are below. There may be changes before you start your course. From May of the year of entry, formal programme regulations will be available in our Programme Regulations Finder.

    Core modules:

    Scalable Machine Learning

    This module will focus on technologies and algorithms that can be applied to data at a very large scale (e.g. population level). From a theoretical perspective it will focus on parallelisation of algorithms and algorithmic approaches such as stochastic gradient descent. There will also be a significant practical element to the module that will focus on approaches to deploying scalable ML in practice such as SPARK, programming languages such as Python/Scala and deployment on high performance computing platforms/clusters.

    15 credits
    Fundamental Security Properties and Mechanisms

    This wide-ranging module covers some fundamental concepts, properties, and mechanisms in security, e.g. identity, authentication, confidentiality, privacy, anonymity, availability and integrity. Cryptographic algorithms are explored together with major attacks (using a break-understand-and-fix approach). High level security protocols are explored (passwords, graphical passwords, key distribution and authentication protocols) together with some rigorous mechanisms for reasoning about their correctness (e.g. belief logics). Other mechanisms such as biometric authentication are also covered.

    15 credits
    Development of Secure Software

    This module covers the security analysis - as well as the secure development - of software-based systems, both on an architectural as well as a system level. The main goal of this module is to teach the foundations of secure software design, secure programming, and security testing. The module requires a solid understanding of software development in general and in particular, of at least one programming language (e.g., Java, JavaScript, Ruby, C#, F#, or C) and basic software development tools such as an IDE (e.g., Eclipse, VS Code), a revision system (e.g., git), or build systems (e.g., Maven, Gradle, npm, FAKE). Moreover, an understanding of database and Web applications is required. The labs require a basic command of Linux in general and the command line (shell) in particular.

    15 credits
    Cyber Threat Hunting and Digital Forensics

    The module provides an in depth view of threat hunting in memory, file system and network data and an introductory analysis of malicious programs. Practical sessions will elaborate on key concepts of incident handling, cyber threat hunting and digital investigation along with detailed analysis of real world case studies. We will also introduce some unusual and non-virulent types of malware.

    15 credits
    Security of Control and Embedded Systems

    This module will explore security issues in systems where computation is carried out to sense, analyse, and control physical system elements. These systems typically react in real time to external events. Examples include washing machines, autonomous vehicles and traffic management systems, power distribution systems, automated manufacturing systems, robotic applications, and web-enabled toys. Many now, or will, operate as part of the 'Internet of Things'. A breach in the security of the systems of interest could also have catastrophic safety consequences. Complications arise when intrusions are detected, e.g., closing down a system may simply not be possible.

    15 credits
    Text Processing

    This module introduces fundamental concepts and ideas in natural language text processing, covers techniques for handling text corpora, and examines representative systems that require the automated processing of large volumes of text. The module focuses on modern quantitative techniques for text analysis and explores important models for representing and acquiring information from texts. You should be aware that there are limited places available on this course. 

    15 credits
    Machine Learning and Adaptive Intelligence

    The module is about core technologies underpinning modern artificial intelligence. The module will introduce statistical machine learning and probabilistic modelling and their application to describing real-world phenomena. The module will give students a grounding in modern state-of-the-art algorithms that allow modern computer systems to learn from data. It has a considerable focus on the mathematical underpinnings of key ML approaches, requiring some knowledge of linear algebra, differentiation and probability.

    Students should be aware that there are limited places available on this module.

    15 credits
    Natural Language Processing

    This module provides an introduction to the field of computer processing of written natural language, known as Natural Language Processing (NLP). We will cover standard theories, models and algorithms, discuss competing solutions to problems, describe example systems and applications, and highlight areas of open research. You should be aware that there are limited places available on this module.

    15 credits
    Cybersecurity and AI Dissertation Project

    For your individual project you can choose from a wide range of possibilities in many different environments both within, and outside, the University. The project is completed during the summer and you will have a personal academic supervisor to guide you during this period. The individual project is examined by a dissertation based on the project work and an oral examination. This module has been designed for students taking the MSc Cybersecurity and AI programme; the topic will be at the interface of Cybersecurity and AI. This provides a significant element of glue, bringing together the two areas that make up the programmes.

    60 credits

    The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

    Open days

    An open day gives you the best opportunity to hear first-hand from our current students and staff about our courses.

    You may also be able to pre-book a department visit as part of a campus tour.Open days and campus tours


    1 year full-time


    We use lectures, online technical content, tutorials, practical lab sessions and seminars led by staff from external organisations.


    Assessment is by formal examinations, coursework, mini team project, practical assessment, podcast and poster development, and a research project dissertation.


    Department of Computer Science

    Our masters courses at the University of Sheffield cover both the strong theoretical foundations and the practical issues involved in developing software systems in a business or industrial context.

    Our graduates are highly prized by industry, and provide the opportunity for you to gain an advantage in the job market, whether in the UK or overseas.

    Although it is possible to discuss many of the practical issues involved in industrial applications in lectures and seminars, there is no substitute for first-hand experience.

    We have a unique track record in developing innovative project-based courses that provide real experience for computing students, and this experience is embodied in our MSc courses.

    Our MSc programmes last 12 months, and begin in late September. You will study taught modules during two 15-week semesters. Your work is assessed either by coursework or by formal examination. During the summer you complete an individual dissertation project, which may be based within the University or at the premises of an industrial client.

    Entry requirements

    Minimum 2:1 undergraduate honours degree in computer science or a numerate discipline with experience of software systems development.

    We also consider a wide range of international qualifications:

    Entry requirements for international students

    Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.

    Pathway programme for international students

    If you're an international student who does not meet the entry requirements for this course, you have the opportunity to apply for a pre-masters programme in Science and Engineering at the University of Sheffield International College. This course is designed to develop your English language and academic skills. Upon successful completion, you can progress to degree level study at the University of Sheffield.

    If you have any questions about entry requirements, please contact the department.


    We use a staged admissions process to assess applications for this course. You'll still apply for this course in the usual way, using our Postgraduate Online Application Form.

    Apply now


    +44 114 222 1800

    Any supervisors and research areas listed are indicative and may change before the start of the course.

    Our student protection plan

    Recognition of professional qualifications: from 1 January 2021, in order to have any UK professional qualifications recognised for work in an EU country across a number of regulated and other professions you need to apply to the host country for recognition. Read information from the UK government and the EU Regulated Professions Database.