1. Develop and articulate technological or/and non- technological approaches to addressing challenging business problems.

2. Conduct independent research and inquiry to explore and evaluate AI concepts in diverse business contexts.

3. Critically evaluate and synthesise theories and solutions to derive well- founded business insights.

Teaching/Learning Methods and Strategies

Cognitive skills are developed across the modules within the degree programme. Students develop skills in bridging theory with business problem solving, logical reasoning, and critical thinking.
Independent enquiry, critical evaluation and interpretation, abstraction, and assimilation are key elements within the programme. Self- assessment, peer review, and reflection are developed within the individual/group work assignments.
Cognitive skills are developed through AI- focused case studies, role plays, scenario planning, and other interactive teaching methods and learning approaches that foster deep understanding of AI tools for business applications.

Methods of Assessment

Assessment of cognitive skills occurs in the form of group presentations, case studies, simulations and projects.

1. Critically assess the transformative role of AI in business and its broader societal impact.

2. Critically evaluate AI technologies and design thinking principles to inform strategic decision-making in challenging business scenarios.

3. Critically analyse and evaluate the global and cross-cultural implications of AI technologies on business practices and societal structures.

Teaching/Learning Methods and Strategies

The Postgraduate Certificate in AI in Business follows a structured curriculum, focusing on AI’s impact on various industries, ethical considerations, and societal implications. Teaching methods include lectures, interactive workshops, and AI- focused case studies.
Students learn to critically assess various AI tools through hands-on systems, and design thinking exercises.
Understanding the work of managers/firms and assessing their global environment is intrinsic to all teaching and learning opportunities.
Acquisition of knowledge and understanding occurs via structured exposition based on lectures, directed reading of case studies and scholarly journal articles, which are particularly applied to student presentations and group projects, computer-based laboratory work, group work, and private study.
The international dimension to various issues is embedded in modules throughout the course, and concerns around ethics, responsibility, and sustainability are integrated into discussions.

Methods of Assessment

A combination of assessment methods is used to enhance knowledge and understanding including case studies, portfolios, reports, simulations, and projects.

1. Leverage AI/ML to develop actionable insights from data and address challenging business problems.

2. Integrate design thinking and AI-driven models to develop innovative solutions for challenging business problems.

3. Critically evaluate the ethical and responsible management of AI technologies.

Teaching/Learning Methods and Strategies

Students work with real/synthetic datasets, develop/apply AI and ML techniques within a design thinking framework to analyse data and derive actionable insights for business challenges.
Teaching strategies include case study analysis that encourage students to critically assess societal and ethical ramifications of AI in various business contexts.
Teaching is provided through lectures, workshops, directed reading, group work, and computer-based work.
Didactic style approaches will be used to provide knowledge on frameworks, techniques and tools from contemporary research around AI applications in business.
Flipped classroom techniques will be employed, where pedagogically appropriate, to ensure practical understanding of academic research.

Methods of Assessment

The assessment method is formative, continuous and summative, involving continuous assessment in the form of individual and group projects, individual and group oral presentations, case study investigations, reports, computer software simulations, portfolios, and projects.
Formative assessments will be used to provide students with developmental feedback on subsequent assessments.

1. Critically evaluate innovative AI and data analytics techniques to develop sustainable actions that can drive positive impact.

2. Develop and demonstrate organisation and time management skills.

3. Synthesise material from various sources, including journals, data sets, and business reports.

4. Communicate concepts and insights from AI-driven analyses to diverse audiences, including non- specialist audiences.

Teaching/Learning Methods and Strategies

Transferable skills development will permeate the teaching and learning throughout the degree programme. Successful completion of coursework requires students to gather information from a range of sources, including academic journals, industry reports, and real-world data sets, select and assimilate relevant information, and to complete tasks within agreed deadlines that are communicated well in advance.
Students participate in group discussions in class using scenario and role-based approaches that enable cross cultural learning and foster collaborative problem-solving using AI-driven insights in business contexts.
Socratic-based methods will be employed to ensure student discussion, debate and critical reflection, engaging with important theories and their application. This approach encourages students to critically evaluate and communicate the implications of AI in business, exploring ethical considerations and innovative strategies for deploying AI in business settings.

Methods of Assessment

Assessment of coursework requires students to use a range of media (e.g., open-source code-free software, GenAI tools, Microsoft Office tools) to demonstrate their learning. Completion of the final capstone develops skills in independent research inquiry, problem-solving, data synthesis and analysis, and effective presentation, all through a practice-based approach that integrates AI and business strategy.