(Award available for year: Master of Science)
MSc Subject Specific Learning Outcomes:
1. Demonstrate critical analysis by conducting research and performing in-depth analysis to frame business problems, interpret AI model outputs and evaluate their impact on how organisations operate, compete and create value to support managerial and organisational decision-making.
2. Exhibit digital capabilities, including proficiency in artificial intelligence and digital competence, to be able to analyse and appraise the value, risks, limitations, and governance implications of AI systems, and communicate recommendations to diverse stakeholders.
3. Show global career readiness by applying professional skills, effective communication, teamwork, inclusivity, and intercultural competence to evaluate the societal, ethical, legal, and economic impacts of AI adoption and its implications for work, regulation, and organisational responsibility.
4. Demonstrate values-oriented awareness, encompassing ethics, integrity, sustainability, collaboration, compassion, and inclusivity, by designing and justifying responsible AI adoption and digital transformation initiatives within organisations.
5. Engage independently and collaboratively with interdisciplinary teams and external stakeholders to scope, design, and deliver substantial AI-related projects in business contexts through an applied project or dissertation.
Competence Standards
1. Effectively communicate key ideas, theories, problems and challenges in AI and business.
2. Demonstrate analytical and critical thinking skills required to understand business interactions with artificial intelligence.
3. Work collaboratively and effectively with peers using appropriate support when necessary.
4. Working with supervisory support, produce original research or complete a project using a range of social science research skills and methods.
5. Demonstrate knowledge of ethics, responsibility, cultural awareness and community, which govern the responsible use of AI.
Skills Learning Outcomes:
1. Competence in digital and non-digital research strategies, including archival digital methods and causal inference techniques.
2. Advanced analytical skills, including the interpretation of complex machine learning algorithms and AI systems.
3. Gain proficiency in a variety of research methods, enabling the planning and delivery of AI solutions that bridge theory and practical business needs.
4. Effective project management abilities, from scoping and planning to delivery and reporting on practical or theoretical business projects.
5. Academic writing and critical thinking skills, demonstrated through the creation of independent reports, dissertations, and presentations.
A range of assessments will be utilised in assessing student outcomes, these include exams, coursework essay, group presentations, individual reports, projects, and dissertations. An assessment map has been created to understand the variety and extent of coursework.
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