Here is a guide to the subjects studied on this course.
Courses are continually reviewed to take advantage of new teaching approaches and developments in research, industry and the professions. Please be aware that modules may change for your year of entry. The exact modules available and their order may vary depending on course updates, staff availability, timetabling and student demand. Please contact the course team for the most up to date module list.
Year one
Software Development I
Year: 1
Status: C
This module provides students of computing with an initial competence in the development of software through the medium of a modern programming language with facilities for both structured and object-oriented programming
Software Development II
Year: 1
Status: C
This module is a direct follow-on to Software Development I. Students are introduced to more advanced features of both an algorithmic programming language and an object oriented language, and will be expected to acquire a higher level of competence in writing software.
Database Systems
Year: 1
Status: C
The module covers the fundamental principles and theory of database design and provides practical experience in designing and developing database systems using a range of techniques, tools and technologies. It emphasises the important role of databases within an organisation and addresses the use of scalable and secure relational database management systems to facilitate the development of software systems involving large volumes of data and over the web.
Artificial Intelligence I
Year: 1
Status: C
In this module, students will gain an understanding of the foundations, methodologies, and technological applications of AI technologies and algorithms. They will help them develop their ability to apply these to the design and implementation of AI models using code.
Discrete and Numerical Mathematics
Year: 1
Status: C
This module builds foundational skills in discrete and numerical mathematics for computing and data science. Students develop practical skills in logic, combinatorics, numerical methods, and error analysis, with applications in AI, cybersecurity, finance, and engineering. Ethical issues, computational errors, and real-world impacts are also explored through hands-on coding and case studies.
Symbolic and Analytic Mathematics
Year: 1
Status: C
This module provides a comprehensive introduction to symbolic and analytical mathematics, focusing on calculus and foundational algebra. Students gain mathematical reasoning and problem-solving skills, essential for understanding complex mathematical structures and functions. The module explores calculus techniques such as differentiation and integration, emphasising their application in optimisation problems, which are foundational in machine learning, data analysis, and numerical optimisation. By integrating these techniques with algebraic manipulation and symbolic computation using tools like SymPy, students develop the analytical tools needed for advanced studies in linear algebra, calculus, and probability theory, preparing them for real-world challenges in data science, artificial intelligence, and scientific computing.
Year two
Cloud Computing
Year: 2
Status: C
This module explores a range of modern development and deployment concepts in the context of scalable and high performance cloud and distributed computing systems.
The module combines the study of the key theoretical concepts of Cloud Computing and Distributed Computing development techniques, with practical based industry focused problems, enabling the student to translate the associated theoretical concepts into practical implementation. The module provides an understanding of the role and function of the core technologies involved and address the design principles required for development.
Cyber Risk Management, Ethics & Governance
Year: 2
Status: C
This module provides students with a comprehensive understanding of cyber risk management, emphasising ethical considerations and governance frameworks essential for modern organisations. Students will explore the evolving landscape of cyber threats, learn to assess and mitigate risks and examine ethical dilemmas in data privacy and incident response. Through case studies and practical applications the module equips students with the skills to develop robust cybersecurity strategies that align with regulatory standards and best practices, preparing them for roles in cybersecurity governance, compliance, and risk management.
Object-oriented Programming
Year: 2
Status: C
This module builds on knowledge and skills attained in previous modules, i.e., core programming concepts and capabilities involving loops, conditions, functions, problem-solving, design, and logical thinking.Typically, a student's first exposure to programming in our degree is with Java, and in this module will have an opportunity to learn a new language (e.g., C#, C++, or Python).
Students will have an opportunity to increase their coding skills and learn about more complex programming and software engineering concepts such as Object Orientation, Decomposition, Functional Programming, Memory Management, Input/Output, Exception Handling, Testing, Debugging, and Version Control. Students will design and implement code solutions to set problems both individually and in groups.
Algorithms and Data Structures
Year: 2
Status: C
The module builds upon the expertise acquired in Year 1 software development. Students are introduced to the classic data structures and algorithms that are used to process them, the specification of methods and classes and the measurement of algorithm performance.
Professional Development
Year: 2
Status: C
This module is designed to equip students with the appropriate research and transferable skills needed to secure employment within the Computing and Engineering domain.
The module prepares students for professional work by developing knowledge of the responsibilities and obligations of employees, employers and clients as determined by codes of professional conduct. Students will have the opportunity to practise the presentation of themselves in, for example, application forms, curriculum vitae, interview, elevator pitches and aptitude tests.
The module provides an underpinning foundation of research concepts, methods and techniques necessary for project development and delivery. The students employ research skills developed during the module to gather research from a variety of sources and critically review this literature. Embedded in all these activities is the reinforcement of the need for adhering to recognised ethical standards and taking a professional approach to employability.
Linear Algebra
Year: 2
Status: C
This module builds foundational skills in linear algebra for technology, engineering, and data science careers. Students explore vectors, matrices, decomposition, eigenvalues, and orthogonality, applying them to real-world problems like machine learning, optimisation, and data fitting. Emphasis is placed on problem-solving, analytical thinking, and practical use of modern computational tools.
Probability and Statistics
Year: 2
Status: C
This module builds a strong foundation in probability and statistics for data science, AI, and decision-making. Students develop skills in data analysis, inference, hypothesis testing, and regression, using Python for statistical computing. Real-world problem-solving and hands-on projects reinforce theory, fostering critical thinking and analytical abilities for advanced study and professional roles.
Year three
International Academic Studies
Year: 3
Status: C
This module provides an opportunity to undertake an extended period of study outside the UK and Republic of Ireland. Students will develop an enhanced understanding of the academic discipline whilst generating educational and cultural networks.
Professional Practice - Computing
Year: 3
Status: C
This module provides undergraduate students with an opportunity to gain structured and professional work experience, in a work-based learning environment, as part of their planned programme of study. This experience allows students to develop, refine and reflect on their key personal and professional skills. The placement should significantly support the development of the student's employability skills, preparation for final year and enhance their employability journey.
Year four
Computer Vision
Year: 4
Status: C
This module provides a foundation in the concepts and techniques used in vision systems. Vision systems is a rapidly expanding field and, as such, has applications in areas such as medical imaging, biomedical sciences, factory automation, autonomous vehicle, facial recognition software and manufacturing. The module provides students with the opportunity of studying a subject area that is at the forefront of developing state-of-the-art advances in technology.
Final Year Project
Year: 4
Status: C
Students are required to undertake a major project during the final year of the course. The module offers students an opportunity to develop a realistic and meaningful piece of work during their final year. This module allows a chosen subject area to be researched in depth and a solution developed as a consequence. Students will have the opportunity to integrate and apply the learning achieved from other modules in the course. The module runs during both semesters and allows students to develop a comprehensive approach to all aspects of working on a large project. The project encourages innovation and creative thinking in the development of the solution. It also develops the entrepreneurial mindset, which can influence the challenges undertaken and final decisions made.
Mathematical Foundations of Neural Networks
Year: 4
Status: C
This module explores the mathematical foundations of AI, covering multivariable calculus, linear algebra, and optimisation. Students apply theory to real-world problems through mathematics, coding and project options, developing skills in algorithm design and model optimisation. The module builds critical thinking, collaboration, and practical expertise for careers in AI and machine learning.
Computational Methods for Intelligent Systems
Year: 4
Status: C
This module provides a rigorous foundation in matrix methods and numerical techniques, with a strong emphasis on learning from data and computational efficiency. Through interactive and applied learning, students develop problem-solving, analytical thinking, and data-handling skills, preparing them for complex computational and analytical challenges.
By integrating matrix factorisation, discrete calculus, and numerical methods, the module equips students with the tools needed to optimise algorithms, process large-scale data, and enhance computational performance in AI, machine learning, and intelligent systems. Students will engage in practical problem-solving, fostering collaborative and innovative capabilities essential for careers in data-driven industries.
Concurrent and Distributed Systems
Status: O
Year: 4
This module is optional
This module provides a theoretical foundation in the area of concurrent and distributed systems. This is an increasingly important area of computing as these types of systems are now manifest in a wide range of internet/intranet based application domains. The module first covers the key theory and design principles and then provides a learning path for software development in this exciting and evolving area of computing/engineering. As a consequence it facilitates students to develop expertise in the core skills area of multithreaded, networked and web-enabled computer systems.
Computational Intelligence Technology
Status: O
Year: 4
This module is optional
This module will provide students with an understanding of the computational intelligence research area. The module addresses both existing techniques used individually and in hybrid forms. The module also introduces the current research topics within this domain, of Fuzzy Logic and Approximate Reasoning and Neuro-computing.
