Introduction
The programme “Professional Mini-Master's in Artificial Intelligence and Its Business Applications” develops professional practice in Mini Professional Master Programmes. It connects the subject with workplace challenges by examining existing evidence and practices and choosing methods appropriate to the organization and its available resources.
The learning progresses from artificial intelligence applications and controls to governance, accountability, and compliance management, with practical work on strategy formulation and prioritization, applied research, evidence development, and recommendations, project planning and implementation control. Participants prepare outputs to support workplace application and review the quality and results of implementation.
Learning objectives
- Design an AI use case with verification criteria and human review in an application related to “Professional Mini-Master's in Artificial Intelligence and Its Business Applications”.
- Translate strategic direction into actionable objectives and initiatives.
- Prepare an applied study connecting the research question, data, analysis, and recommendation.
- Prepare a project plan connecting scope, time, resources, and risks.
- Define decision-making authority, accountability mechanisms, and obligation monitoring.
Learning areas
1. Artificial Intelligence Applications and Controls
- Identify a task that AI can support, and separate inputs and human decisions from outputs produced by the tool.
- Prepare suitable test data and examples while respecting confidentiality, privacy, and permissions, and use de-identified training exercise data.
- Write clear instructions covering the task, context, constraints, and output format, and compare multiple formulations using a fixed set of examples.
- Check outputs for errors, bias, and unsupported information, and identify cases that require specialist review.
- Assess the feasibility of use in terms of quality, time, cost, and risk, and document controls for approval, monitoring, and stopping when failures occur. The application examines a case related to “Professional Mini-Master's in Artificial Intelligence and Its Business Applications”.
2. Strategy Formulation and Prioritization
- Analyze the internal and external environment using available data, and distinguish opportunities from assumptions that require verification.
- Define a specific strategic problem and connect it to the organization's mission and the value sought by beneficiaries and stakeholders.
- Set measurable objectives with a baseline, target, and time horizon, and assign a clear owner to each objective.
- Prioritize initiatives according to impact, feasibility, resources, risks, and interdependencies, explaining the reasons for the trade-offs.
- Build an implementation roadmap covering phases, owners, resources, review gates, and a mechanism for adjusting priorities when circumstances change.
3. Applied Research, Evidence Development, and Recommendations
- Frame a research question or practical problem suitable for study, and define the subject boundaries, context, and outcome the research will support.
- Review sources relevant to the question, assess their reliability and currency, and distinguish direct evidence from opinion and inference.
- Select an appropriate method, instrument, and sample, explaining limitations and obtaining approvals and protecting privacy when collecting data from people.
- Organize and analyze data and relate findings to the question, avoiding generalizations unsupported by the sample or causal conclusions based only on correlation.
- Write specific, actionable recommendations with responsibilities, resources, and indicators, and include source documentation and limitations of conclusions in the applied report.
4. Project Planning and Implementation Control
- Define the project rationale, expected results, stakeholders, and success criteria, and document the scope of work and exclusions.
- Break deliverables into work packages and related activities, and estimate durations, resources, and activity dependencies.
- Prepare a schedule and cost baseline, identify delivery and review milestones, and clarify approval and escalation responsibilities.
- Analyze implementation risks, define responses and warning indicators, and control change requests and their effects on time and cost.
- Build a progress report covering variances, decisions, and lessons learned, and define procedures for accepting deliverables and closing the project.
5. Governance, Accountability, and Compliance Management
- Map decision-making, oversight, and execution levels, and identify separation of roles and potential conflicts of interest.
- Review policies, committees, delegated authorities, and reporting frequency, and connect each responsibility to clear authority and limits.
- Create an obligations register specifying the source, scope, responsible party, and compliance evidence, and review applicable local requirements.
- Define disclosure, accountability, complaint handling, and misconduct reporting mechanisms, and protect information confidentiality during follow-up.
- Assess a practical governance case and prepare a gap remediation plan with review indicators and evidence of action closure.
Practical outputs
- A use case brief and a test template for the quality of AI outputs.
- A strategy map and a priority matrix for proposed initiatives.
- An applied research plan, data collection tool, and findings and recommendations report.
- A project charter, implementation schedule, and change and risk tracking register.
- An authority matrix, obligations register, and escalation and review mechanism.
Who should attend
- Practitioners, specialists and supervisors whose work relates to the programme subject.
- Managers and teams working in mini professional master programmes, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “Professional Mini-Master's in Artificial Intelligence and Its Business Applications” within their organizations.
Prerequisites
- Working familiarity with the programme field and the ability to discuss a professional case or challenge.
- Confirm the suitability of your experience and any specialist prerequisites with the Union before participation.
Conclusion
The programme “Professional Mini-Master's in Artificial Intelligence and Its Business Applications” brings together concepts, case review and a practical application. Participants prepare steps that can be adapted to their responsibilities and organizational resources, with an indicator to follow application and review results after returning to work.
Participation arrangements and any special requests are specified in the confirmation issued by the Union.