Compulsory modules

Dissertation (60 credits)

The aims of this module are to give the student the opportunity to study a subject, business problem or research question in depth and to research the issues surrounding the subject or background to the problem.

The module will equip the student with the relevant skills, knowledge and understanding to embark on their individual research project and they will be guided through the three options available to them to complete their dissertation:

  • A desk based research project that could be set by an organisation or could be a subject of the student's choice.
  • A project that involves collection of primary data from within an organisation or based on lab and/or field experiments.
  • A full professional placement within an organisation during which time they will complete a project as part of their role in agreement with the organisation (subject to a suitable placement position being obtained).

Students will achieve a high level of understanding in the subject area and produce a written thesis or project report which will discuss this research in depth and with rigour.

Optional modules

Choose one of the following:

Advanced Big Data Analytics (15 credits)

The aims of this module are to:

  • Introduce the concept of big data systems and the challenges posed by such systems.
  • Introduce the requirement of advanced analytics, processing techniques and architectural solutions to tackle the problems encountered.

Human-Computer Interaction (15 credits)

The aim is to provide a foundation for human-centered computing and human computer interaction (HCI) principles in topics including technologies for HCI, human-centered development approaches, interaction and user experience evaluation methodologies, prototyping strategies, and research methods in HCI.

Students will be introduced to a variety of methods for addressing human factors in computing through researching and evaluating approaches for digital interaction.

The module will also provide a foundation for students to evaluate user needs in digital technology development and broader social impacts around digital innovation in-practice.

Students will engage with HCI discussion and dissemination in giving and evaluating research poster presentations.  

Choose one of the following:

Information Systems Security (15 credits)

The aim of this module is to provide the students with the necessary knowledge and technical details of information systems security properties, mechanisms, protocols, management and applications that are widely in use.

Reinforcement Learning (15 credits)

The aims of this module are to:

  • Introduce students to the concepts of data driven decision making and their use in Artificial Intelligence (AI).
  • Enable students to experiment with reinforcement learning and develop different algorithms for applications that require automatic control.

Generative Artificial Intelligence and Large Language Models (15 credits)

This module aims to provide a comprehensive understanding of the principles, architectures, and applications of Generative Artificial Intelligence (AI) and Large Language Models (LLM).

It equips students with the knowledge and skills to design, implement, and evaluate generative models for text and image generation. Students will explore the evolution of neural networks, probabilistic and transformer-based models, and gain practical experience in applying tools and frameworks for developing generative AI systems.

The module also enables students to critically assess the ethical, social, and technical implications of deploying large-scale generative models across diverse domains.

Choose one of the following:

Cybersecurity and Forensics (15 credits)

The aims of this module are to develop students' knowledge and understanding of cybersecurity incidents and processes required for the digital investigation involved aftermath of cyberattacks and cybercrimes.

Applied Data Science and Data Visualisation (15 credits)

The aims of this module is to equip students with advanced programming skills necessary for developing artificial intelligence systems, and for visualising big datasets.

Choose one of the following:

Collaborative Project (15 credits)

The aims of this module are to:

  • Provide students with an opportunity to be exposed to project-based teamwork in diverse settings (understood in this context as involving a range of multidisciplinary, multicultural and demographic elements in differing configurations), aiming to strengthen their cooperative and collaborative working skills and competence, while raising awareness and appreciation of diversity itself.
  • Provide students with hands on experience of identifying, framing and resolving practice oriented and real-world based challenges and problems, using creativity, critical enquiry and appropriate tools to achieve valuable and relevant solutions.
  • Support the development of students' ability to engage in critical enquiry and individual reflection, as well as to apply individual strengths and skills, building on their own educational backgrounds.
  • Provide students with opportunities for networking with stakeholders, organisations and corporations, aiming to enhance the competence and skills needed to connect to relevant parties and build up future professional opportunities.

Cloud applications and services (15 credits)

The aim of this module is to provide the students with an overview of the cloud technology with a special emphasis on cloud applications and the associated challenges.