Postgraduate in Public Policies and Data Intelligence
Education objectives
- Understanding the fundamental principles of public policies and its connection to data science;
- Applying advanced analytical techniques to support the formulation and evaluation of public policies;
- Integrating artificial intelligence and machine learning approaches into evidence-based policy development;
- Implementing data governance models to optimize public management and transparency;
- Assessing the impact of public policies using quantitative and qualitative methods;
- Understanding the ethical and legal implications of using data in public policy;
- Developing strategic skills for managing innovation and digital transformation in public administration.
General characterization
DGES code
4985
Cicle
Master (2nd Cycle)
Degree
Mestrado
Access to other programs
This Master Degree gives access to a Doctoral Program.
Coordinator
Available soon
Opening date
September 2026
Vacancies
30
Fees
12.000 euros for applicants with a nationality from a European Union member country. 15.000 euros for applicants of other nationalities.
Schedule
Mondays 9AM to 6PM
Teaching language
Portuguese
Degree pre-requisites
To complete the curricular component, students must obtain a minimum of 30 ECTS. The curricular part of the programme takes place over the course of one semester.
The award of the Masters degree requires the completion of a final project, carried out during the second semester of the programme, corresponding to 30 ECTS.
Conditions of admittance
The access conditions defined in the legislation in force are taken into account, plus the following specific conditions: - Holders of a bachelor's degree; - Proficiency in English; - Relevant professional experience of at least 5 years in the field of training of the course or in related fields. Applicants who meet the academic and curricular requirements will be selected based on professional experience, academic performance, candidate motivation and, if necessary, an interview. Preference will be given to professionals in Public Administration, Economics, Management, Political Science, Statistics, Engineering, and Information Management who aim to deepen their competencies in data-driven public policy and analytical approaches. Applications: For an application to be considered complete, it is necessary to fill out the form available on the NOVA IMS Applications Portal, upload the Curriculum Vitae (CV) and the Degree Certificate, pay the application fee (51 euros), and submit the process. The selection of candidates is carried out through the assessment of the prerequisites as well as the academic and professional background. The Selection Jury may decide to invite candidates to a preliminary screening interview. Candidates who successfully pass this stage will always proceed to an interview with the program coordinator(s), which is a mandatory step in the admission process. Applications for the 2026/2027 academic year open on January 1, 2026, and will remain open until all available places have been filled. For more information, please consult the NOVA IMS website: https://novaims.unl.pt/en/education/programs/executive-education/executive-master-s-programs/
Evaluation rules
The assessment method will be continuous assessment, carried out through individual or group assignments, projects, quizzes, tests/exams, among others. It is the responsibility of each course instructor to define, at the beginning of each academic year, the assessment method to be applied in their respective curricular units. This information is then made available through the student platform.
Structure
| 1 year - Mandatory | ||
|---|---|---|
| Code | Name | ECTS |
| 200371 | Impact Evaluation and Artificial Intelligence Impact Evaluation and AI | 4 |
| 200372 | Smart and Sustainable Cities and Territories | 4 |
| 200373 | Data Science for Public Policies | 4 |
| 200374 | Policy and Service Design | 4 |
| 200375 | Data Governance | 4 |
| 200326 | New Horizons | 3 |
| 200377 | Public Policies Capstone | 4 |
| 200376 | Smart Regulation | 4 |
| 200334 | Final Work Project | 30 |