Introduction
The programme “Professional Mini-Master's in Digital Project Management Using Artificial Intelligence” 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 applied research, evidence development, and recommendations, with practical work on project planning and implementation control, designing digital transformation and developing services, strategy formulation and prioritization. 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 Digital Project Management Using Artificial Intelligence”.
- Prepare a project plan connecting scope, time, resources, and risks.
- Assess digitization opportunities and define implementation requirements that improve a service or process.
- Translate strategic direction into actionable objectives and initiatives.
- Prepare an applied study connecting the research question, data, analysis, and recommendation.
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 Digital Project Management Using Artificial Intelligence”.
2. 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.
3. Designing Digital Transformation and Developing Services
- Distinguish information digitization, step automation, and business model transformation, and identify the problem targeted by the digital intervention.
- Map the beneficiary journey, touchpoints, and repeated data requests, and identify opportunities for simplification before selecting technology.
- Analyze readiness across procedures, skills, data, and technical infrastructure, and document gaps and dependencies on existing systems.
- Specify solution, integration, access permission, usability, and accessibility requirements, and establish testable acceptance criteria.
- Design a limited-scope pilot with indicators for time, quality, and use, and define conditions for continuing, adjusting, or stopping.
4. 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.
5. 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.
Practical outputs
- A use case brief and a test template for the quality of AI outputs.
- A project charter, implementation schedule, and change and risk tracking register.
- A digital transformation roadmap covering the beneficiary journey and implementation requirements.
- A strategy map and a priority matrix for proposed initiatives.
- An applied research plan, data collection tool, and findings and recommendations report.
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 Digital Project Management Using Artificial Intelligence” 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 Digital Project Management Using Artificial Intelligence” 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.