Course Information course information
About
The rapidly growing field of artificial intelligence (AI) has the potential to revolutionise UK organisations by enhancing efficiency, productivity, innovation, and competitiveness. As AI evolves, so does the regulatory environment, addressing challenges like bias, transparency, and data privacy. Effective governance and regulation are crucial to ensure AI aligns with human rights, democracy, and security. Responsible AI involves designing, developing, and deploying AI systems that are safe, fair, transparent, and compliant with laws. This responsibility falls on developers, organisations, and regulators. There is a growing demand for professionals skilled in ethical AI, particularly in compliance, regulation, and leadership roles.
The target audience of the MSc Ethical and Responsible AI is non-specialist. Students can enrol from successful completion of any primary UG Honours degree subject. This course will differ from other AI courses since it will focus not only on AI techniques, programming, and emerging technologies, but just as importantly on the significance of ethical skills required for the AI technologies sector.
If you are interested in shaping the future of Ethical and Responsible AI to master compliance, regulation, and innovation with ethical expertise, then this is the course for you.
Attendance: Part-time only
The course will be delivered through a hybrid learning model, combining both on-campus and online delivery. Each module will typically include four on-campus sessions, each lasting three hours, spread across a 12-week semester. The remaining module content will be delivered online.
Start Date
September 2025 (Part-Time)
Duration
Part-Time: Students study at least one module per semester, with the flexibility to complete the course over up to three years. Each semester lasts 12 weeks.
Teaching, learning and assessment
All modules are assessed entirely through coursework, with the workload evenly distributed across the semester. Assessments include presentations, software demonstrations, reflective assignments, and a teamwork poster. The MSc research project allows students to tackle real-world AI ethics challenges, focusing on governance, algorithmic bias, explainability, and regulatory compliance - delivering valuable insights to their chosen sector.
This course uses a hybrid teaching approach. Each semester, students attend four on-campus sessions, while the remaining learning is conducted online via video and audio recordings, interactive quizzes, and educational apps. Lecture materials, including PowerPoint presentations, are made available for review and revision on the University’s online learning system.
Career Options
Graduates with an MSc in Ethical and Responsible AI will have a range of job opportunities in Northern Ireland and the UK. In Northern Ireland, companies such as the BT Ireland Innovation Centre and PwC’s Advanced Research and Engineering Centre are prominent employers seeking AI professionals with a focus on ethics. These organisations are involved in cutting-edge AI research and development, providing roles for AI Ethics Consultants, Data Scientists, and AI Policy Advisors.
In the broader UK market, tech giants such as Google DeepMind, IBM, Microsoft, and Accenture are leading the way in ethical AI. These companies require professionals who can ensure their AI systems are developed and deployed responsibly. Roles in these companies include AI Research Scientists, AI Developers, and AI Consultants, focusing on integrating ethical considerations into AI technologies. The financial sector, healthcare, and government agencies also offer significant opportunities for AI professionals to work on ethical AI projects, ensuring compliance with regulations and promoting fair practices.
Job Roles
There are job roles within these companies including AI Research Scientists, AI Developers, and AI Consultants, focusing on integrating ethical considerations into AI technologies and ensuring fairness and transparency in data practices, advising on AI policy, and conducting research on AI's ethical implications. The financial sector, healthcare, and government agencies also offer significant opportunities for AI professionals to work on ethical AI projects, ensuring compliance with regulations and promoting fair practices.
Graduate Employers
Graduates of an MSc in Ethical and Responsible AI have a wide array of potential employment opportunities in both Northern Ireland and the UK. They can take up roles such as AI Ethics Consultants, Data Scientists, AI Policy Advisors, Researchers, and AI Developers. These positions are available within technology companies, government agencies, research institutions, and consulting firms. The demand for professionals who can navigate the ethical implications of AI technologies is growing, making these roles relevant, essential, and financially rewarding.
Further study and training opportunities are also available for graduates. Students can opt for PhD programs in AI ethics, machine learning, or related fields to deepen their expertise. Additionally, professional certifications in data ethics, AI governance, or cybersecurity can enhance student qualifications.
Contact
School of Computing, Engineering and Intelligent Systems
Email: sceis@ulster.ac.uk
Modules
Ethics and Governance in Artificial Intelligence
This module offers a comprehensive exploration of Artificial Intelligence (AI) with a specific focus on Ethical and Responsible AI principles and practices. Students will examine real-world case studies and regulatory frameworks to critically assess the ethical implications of
AI technologies across diverse sectors. Through engaging with concepts such as trust, fairness, transparency, and accountability, students will develop critical thinking, problem solving, and communication skills essential for evaluating and contributing to the development of safe, ethical, and socially responsible AI solutions in professional contexts.
Fundamentals of Artificial Intelligence
This module provides students with a case-based approach to understanding and applying fundamental AI technologies. Through practical, non-programming methods, students will develop an appreciation of data value, bias, and the methodologies of supervised and unsupervised learning, including classification, predictive analytics, and pattern detection.
The module emphasises the importance of using a structured lifecycle to create AI models and critically evaluate their responsibility, suitability for deployment, and interpretability.
Students will gain practical insights into responsible AI applications through real-world case studies across diverse business contexts.
Applied Artificial Intelligence in Ethical Contexts
This module provides the student with an industry-focused approach to understanding and applying AI technologies without requiring AI programming experience. Students will explore how AI models are designed, trained, deployed, and optimised within real-world scenarios.
Since AI is a rapidly evolving field, the module content will be continually updated with current research, industry innovations, and emerging AI technologies, as advised by real-world case studies, allowing students to stay at the forefront of AI advancements.
Introduction to Data Science
This module serves as an entry point into the exciting field of data science, specifically tailored for individuals with no prior programming or data science experience. Throughout the module, students will acquire a strong foundation in fundamental concepts and techniques essential to data science. Key areas covered include data collection, processing, analysis, and visualisation. Additionally, students will receive an introduction to the fundamental principles of computer programming within data science. This encompasses understanding syntax, data structures, programming terminology, techniques, libraries, and core concepts. By the end of this module, students will have developed proficiency in core data science techniques, blending theoretical learning with practical exercises using a common data science programming language.
Management of Change
Organisational change is a complex challenge that requires careful planning, execution, and adaptation. This module delves into the intricacies of organisational change, focusing on understanding the underlying dynamics that influence successful transformation. It will evaluate various change management models, examining their application and effectiveness in different organisational contexts.
Participants will explore the role of cultural factors in driving or hindering change, considering how organisational culture, leadership, and communication impact the success of change initiatives. The module also highlights best practices for leading and managing change, providing practical tools and strategies that can be applied to overcome common barriers such as resistance, lack of engagement, and misalignment with organisational goals.
By the end of the module, participants will have a better understanding of how to navigate the complexities of change, equipping them with the knowledge and skills to contribute to successful transformation efforts in their organisations.
Responsible Artificial Intelligence in Practice
Artificial Intelligence is revolutionising industries, increasing efficiency, and encouraging innovation. However, its widespread adoption also brings significant risks, such as bias in decision-making, lack of transparency, accountability gaps, and regulatory challenges. This module focuses on the practical application of responsible AI principles, ensuring AI systems are developed and deployed with fairness, transparency, and accountability. Students will engage with real-world challenges such as bias mitigation, explainability, and accountability mechanisms, gaining practical skills to make AI systems responsible. They will learn how to identify and mitigate biases in AI systems and understand the tools and guidelines that support responsible AI practices.
Masters Project (Research)
The aim of the project is to allow the student to demonstrate their ability to undertake an independent research project that can either involve the design and implementation of AI based solutions or a critical research investigation into AI governance, ethics, and policy.
Development-based projects will require students to design, develop, and evaluate AI solutions, incorporating ethical considerations and governance frameworks into their solution's design and implementation. Research-based projects, on the other hand, will focus on investigating AI ethics, governance, legal frameworks, or responsible AI adoption, producing a thorough research study and offering insights into policy or regulatory aspects.
In summary the masters project represents a piece of work performed by the student under suitable staff supervision which draws from both the practical application of AI-based solutions and the scholarly investigation of AI-related issues. The project will require students to critically evaluate the subject area, demonstrate originality, and provide a thoughtful analysis of their findings, ensuring strong ethical considerations are embedded throughout.
Entry Requirements
Academic qualifications
Applicants must:
(a) have gained
(i) a second-class honours degree or better, from a university of the United Kingdom or the Republic of Ireland, or from a recognised national awarding body, or from an institution of another country which has been recognised as being of an equivalent standard; or
(ii) an equivalent standard (normally 50%) in a Graduate Diploma, Graduate Certificate, Postgraduate Certificate or Postgraduate Diploma or an approved alternative qualification.
iii) the content of the qualification presented (as described in (i) may have a maximum of 50% computing content.
Eligibility
Places are limited and open to applicants who:
- are over 18 years of age;
- are eligible to work in Northern Ireland;
- are ‘settled’ in Northern Ireland, and has been ordinarily resident in the UK for at least three years; or
- are a person who has indefinite leave to enter or remain in the UK.
- meet the course specific entry requirements. See course pages for requirements.
- meet the Ulster University general entry requirements
