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Master’s in Data Engineering, Policy & Regulation

Online master's programme of 1,900 hours in data, policy and regulation engineering. 12 modules covering urban data governance, data platforms, data protection, European data and AI regulation, urban data analysis, evidence-based policy, regulation of urban services, AI in public administration, cybersecurity and urban digital twins, applying the GDPR, the Data Governance Act and Python, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Design urban data governance frameworks.

02

Apply European data and artificial intelligence regulation.

03

Ensure privacy in urban data projects.

04

Analyse urban data with statistical and geospatial techniques.

05

Design evidence-based public policies.

06

Assess the risks of algorithms in public administration.

07

Plan the procurement of urban technology solutions.

Profile

Who it's for

  • Urban policy analysts who want to ground decisions in data.
  • Municipal data managers.
  • Digital regulation consultants.
  • Data protection officers.
  • AI governance specialists.
  • Smart city project managers.
  • Engineering or science graduates seeking to enter public administration.
Standards & tools

What you'll work with

  • Regulation (EU) 2016/679 (GDPR)
  • Organic Law 3/2018 (Spanish data protection and digital rights law, LOPDGDD)
  • Regulation (EU) 2022/868 (Data Governance Act)
  • Regulation (EU) 2023/2854 (Data Act)
  • Regulation (EU) 2024/1689 (Artificial Intelligence Act)
  • Directive (EU) 2019/1024 (open data and re-use of public sector information)
  • UNE 178104 (smart city platforms)
  • Royal Decree 311/2022 (Spanish National Security Framework, ENS)
  • Python (pandas, scikit-learn)
  • QGIS
  • CKAN
  • FIWARE
  • Power BI
Syllabus

12 modules · 1900 h

  1. 1.1Smart city and data city
  2. 1.2The urban data ecosystem
  3. 1.3Data governance in public administration
  4. 1.4European data strategies
  5. 1.5Data spaces and sovereignty
  6. 1.6Provincial councils, city councils and metropolitan areas
  7. 1.7Ethics of urban data
  8. 1.8Digital maturity indicators
  9. 1.9The experiences of Barcelona, Amsterdam and Helsinki
  10. 1.10Case study: data maturity diagnosis of a city council
  1. 2.1IoT sensors and urban networks
  2. 2.2Municipal administrative records
  3. 2.3Mobility and mobile phone data
  4. 2.4City platforms: UNE 178104
  5. 2.5FIWARE and data models
  6. 2.6Open data catalogues
  7. 2.7Semantic data interoperability
  8. 2.8Data quality
  9. 2.9Reference architectures
  10. 2.10Lab: publishing a dataset in a CKAN catalogue
  1. 3.1GDPR in the public sector
  2. 3.2Organic Law 3/2018
  3. 3.3Data protection impact assessments
  4. 3.4Anonymisation and pseudonymisation
  5. 3.5Privacy by design
  6. 3.6Video surveillance and public space
  7. 3.7Location data
  8. 3.8The data protection officer
  9. 3.9Security breaches
  10. 3.10Practical exercise: impact assessment of an urban sensor system
  1. 4.1The Data Governance Act
  2. 4.2The Data Act
  3. 4.3The Open Data Directive
  4. 4.4High-value datasets
  5. 4.5The Artificial Intelligence Act
  6. 4.6The Digital Services Act
  7. 4.7The Interoperable Europe Act
  8. 4.8Data altruism
  9. 4.9Data intermediaries
  10. 4.10Case study: a city council's obligations under the Data Act
  1. 5.1Statistics applied to policy
  2. 5.2Geospatial analysis of services
  3. 5.3Urban time series
  4. 5.4Machine learning in the public sector
  5. 5.5Visualisation and dashboards
  6. 5.6Network analysis
  7. 5.7Natural language processing
  8. 5.8Bias in urban data
  9. 5.9Reproducibility of analyses
  10. 5.10Lab: analysis of municipal service data with Python
  1. 6.1The public policy cycle
  2. 6.2Designing policies with data
  3. 6.3Theory of change
  4. 6.4Monitoring indicators
  5. 6.5Impact evaluation
  6. 6.6Experiments and pilots
  7. 6.7Behavioural economics
  8. 6.8Use of evidence in decision-making
  9. 6.9Communicating with policy-makers
  10. 6.10Workshop: designing a policy with a logical framework
  1. 7.1Theory of economic regulation
  2. 7.2Regulation of network services
  3. 7.3Shared mobility and licensing
  4. 7.4Digital platforms in the city
  5. 7.5Tourist accommodation and platforms
  6. 7.6Urban regulatory sandboxes
  7. 7.7Regulation of urban drones
  8. 7.8Regulatory impact analysis
  9. 7.9Better regulation and simplification
  10. 7.10Case study: regulation of shared e-scooters
  1. 8.1Uses of AI in cities
  2. 8.2Automated decision-making algorithms
  3. 8.3Algorithmic transparency in public administration
  4. 8.4Public algorithm registers
  5. 8.5AI risk assessment
  6. 8.6High-risk systems
  7. 8.7AI governance
  8. 8.8Algorithm auditing
  9. 8.9Participation in algorithmic systems
  10. 8.10Practical exercise: transparency sheet for a municipal algorithm
  1. 9.1The Spanish National Security Framework (ENS)
  2. 9.2The NIS2 Directive and public administrations
  3. 9.3Cybersecurity of urban platforms
  4. 9.4Incident management
  5. 9.5Security in urban IoT
  6. 9.6Continuity of digital services
  7. 9.7The technology supply chain
  8. 9.8Staff awareness
  9. 9.9Security auditing
  10. 9.10Workshop: risk analysis of a city platform
  1. 10.1The concept of the urban digital twin
  2. 10.2CityGML 3D models
  3. 10.3Real-time data integration
  4. 10.4Simulation of policy scenarios
  5. 10.5Twins for mobility and energy
  6. 10.6Participation through twins
  7. 10.7Governance of the twin
  8. 10.8Limitations and costs
  9. 10.9European urban digital twin experiences
  10. 10.10Lab: visualisation of a 3D urban model
  1. 11.1Procurement of urban technology
  2. 11.2Public procurement of innovation
  3. 11.3Vendor lock-in
  4. 11.4Open standards and free software
  5. 11.5Public-private collaboration on data
  6. 11.6Start-ups and urban labs
  7. 11.7European digital funding
  8. 11.8Evaluation of technology projects
  9. 11.9Scaling up solutions
  10. 11.10Case study: tender specifications for an urban data platform
  1. 12.1Selection of the public problem
  2. 12.2Data inventory and quality
  3. 12.3Applicable regulatory framework
  4. 12.4Data analysis
  5. 12.5Policy or regulatory proposal
  6. 12.6Risk and privacy assessment
  7. 12.7Implementation and monitoring plan
  8. 12.8Conclusions and future lines of work
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

The programme is delivered 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so it is compatible with full-time work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (pandas, scikit-learn), QGIS, CKAN, FIWARE and Power BI, in free, academic or evaluation versions. You work on real procedures for municipal service data analysis, data protection impact assessments and policy design with indicators. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: Regulation (EU) 2016/679; Organic Law 3/2018; Regulation (EU) 2022/868; Regulation (EU) 2023/2854; Regulation (EU) 2024/1689; Directive (EU) 2019/1024; UNE 178104; Royal Decree 311/2022.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of the GDPR, Organic Law 3/2018 and the Data Governance Act applied to real cases, not as a theoretical annex.
Industry software:Python (pandas, scikit-learn), QGIS, CKAN, FIWARE and Power BI, in free, academic or evaluation versions.
Master's Thesis with defence:a data-driven policy or regulatory proposal for a real public problem, with data analysis, regulatory and privacy assessment and an implementation plan, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Data inventory and platform
Inventory urban data sources and publish a dataset in a CKAN catalogue.
Privacy impact assessment
Carry out a data protection impact assessment for an urban sensor system.
Data analysis
Analyse municipal service data with Python and geospatial tools.
Policy design
Design a policy with a logical framework and monitoring indicators.
Master's Thesis
a data-driven policy or regulatory proposal for a real public problem, with data analysis, regulatory and privacy assessment and an implementation plan, defended before a panel.
Career opportunities

Where this takes you

Urban policy analystMunicipal data managerDigital regulation consultantData protection officerAI governance specialistSmart city project manager
Admissions & scholarships

Requirements

  • University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • Internet connection and a computer capable of running the programme's software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with Python (pandas, scikit-learn), QGIS, CKAN, FIWARE and Power BI, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A university degree in engineering, science or architecture, or equivalent professional experience, plus a computer able to run the software and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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