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Home   >  Master's & postgraduate courses  >  Education  >  Microcredential in Artificial Intelligence Applied to Construction
  • Presentation
  • Training Content
  • Learning methodology
  • Teaching team
This programme is full up. Open a second group for the year 2025-2026
+ info

Presentation

Edition
2nd
Credits
1.5 ECTS
Type
Microcredential
Delivery method
Live online
Language of instruction
English
Fee
€360 €108(Funded by the Ministry of Science, Innovation and Universities within the framework of the Microcreds Plan. Financing applied to residents in Spain between 25 and 64 years old.)
Notes payment of enrolment fee and 0,7% campaign
Dates
Start date: 15/10/2025
End date: 12/11/2025
Class schedule
Wednesday: 5:00 pm to 8:00 pm
Why this programme?
Generative AI and autonomous agents are reshaping every phase of the construction life cycle, from concept design and planning to on site execution and asset management. This micro credential equips you to leverage that power responsibly. Through hands on labs and real world projects you will learn to:
  • Automate routine tasks and documentation in construction workflows;
  • Create web applications, dashboards reports relevant to project management or asset monitoring without previous coding experience;
  • Choose the right AI model for each task by understanding the strengths and current capabilities of leading tools;
  • Turn emerging techniques such as computer vision and large language models into competitive advantage.
  • Assess ethical, regulatory and sustainability implications;
  • Introduction to workflows with AI agents that link multiple tools through APIs
Promoted by:
  • Uni贸n Europea. NextGenerationEU
  • Ministerio de Ciencia, Innovaci贸n y Universidades
  • Plan de Recuperaci贸n, Transformaci贸n y Resiliencia Gobierno de Espa帽a
  • Next Generation Catalunya
芦Recovery, Transformation and Resilience Plan - Funded by the European Union - Next Generation EU禄. Component 21, investment 6, C21.I06.P02.S04.S05. PROVISIONAL.SI01.
Aims
  • Understand the fundamentals, limits and rapid evolution of generative AI.
  • Optimize schedules, costs and risk management in civil works with AI.
  • Build AECO sector-relevant apps, landing pages and data processing scripts with Python, HTML and AI assistants, no manual coding required.
  • Explore the principles of agentic AI and API integrations for autonomous workflows.
  • Anticipate future AI and civil engineering convergence such as computer vision, digital twins and robotics.
  • Develop a project that tackles a genuine challenge from your professional construction or infrastructure context.
Who is it for?
  • Professionals in Architecture and Engineering.
  • Project managers and management.
  • Specialists in Digitalization and Technology.
  • Management and Control Technicians.
  • Consultants and Auditors.

Training Content

  • Foundations and Context
    • Explore the history of machine learning and current AI applications in civil engineering.
    • Understand the importance of the AI “black box” in engineering contexts.
    • Get hands-on with text and image generation tools and learn strategies to keep skills up to date.

  • Generative AI for Project Management
    • Work on a guided project using tools like Gemini, ChatGPT, Grok, Claude or Perplexity to draft detailed work plans.
    • Apply prompt engineering to build and refine an AI “copilot” template.
    • Generate activity lists, work plans, deliverables and milestones from initial project objectives.

  • Programming with AI Assistants
    • Learn to create landing pages, micro apps and data pipelines using Python and HTML, without prior coding experience.
    • Use AI assistants to generate, debug and optimize code effectively.
    • Build confidence in developing custom productivity tools supported by AI.

  • Introduction to Agentic AI, Prompt Engineering and APIs
    • Get an overview of autonomous agents and emerging “agentic spaces” through platforms like N8N, Google Agentspace, Firebase Extensions, and Vertex AI Agent Builder.
    • Understand how prompt engineering influences agent behavior in automated workflows.
    • Learn how API keys enable connections between diverse tools and services in a pipeline

  • The Road Ahead: AI and Civil Engineering
    • Preview future applications like computer vision for inspection using YOLO v11, and the role of robotics and edge AI on construction sites.
    • Examine the sustainability impacts of AI integration in civil engineering.
    • Review upcoming EU and ISO standards along with key ethical considerations.

  • Final Project
    • Receive one-on-one guidance from the start to define a real-world problem, assess feasibility, and develop a proof of concept or roadmap using appropriate models and data sets.
    • Present the final project and benefit from peer feedback to reinforce learning and practical application.
Degree
Microcredential. Europass digital credential in Artificial Intelligence Applied to Construction Engineering: Enhancing Productivity and Efficiency issued by the Universitat Polit猫cnica de Catalunya.

Learning methodology

The teaching methodology of the programme facilitates the student's learning and the achievement of the necessary competences.

  • Exhibition sessions of content.
  • Problem-based learning.
  • Learning based on challenges.


Assessment criteria
Attendance
At least 80% attendance of teaching hours is required.
Solving exercises, questionnaires or exams
Individual tests aimed at assessing the degree of learning and the acquisition of competences.
Work out projects
Studies on a specific topic, by individuals or groups, in which the quality and depth of the work is assessed, among other factors.
Virtual campus
The students on this microcredential will have access to the My_ Tech_Space virtual campus - an effective platform for work and communication between the programme's students, lecturers, directors and coordinators. My_Tech_Space provides the documentation for each training session before it starts, and enables students to work as a team, consult lecturers, check notes, etc.

Teaching team

Academic management
  • Komarizadehasl, Seyedmilad
    info
    / / /
    PhD in Construction Engineering from the UPC. Master in Structural Engineering from the University of Tehran and graduated in Civil Engineering from KNTU. Lecturer in the Department of Civil and Environmental Engineering at the UPC and member of the EC-Building Engineering group. He has participated in projects such as Erasmus Mundus NoRisk and has been a guest lecturer in Tongji. His research focuses on SHM, AI, BIM and structural analysis.
Teaching staff
  • Komarizadehasl, Seyedmilad
    info
    / / /
    PhD in Construction Engineering from the UPC. Master in Structural Engineering from the University of Tehran and graduated in Civil Engineering from KNTU. Lecturer in the Department of Civil and Environmental Engineering at the UPC and member of the EC-Building Engineering group. He has participated in projects such as Erasmus Mundus NoRisk and has been a guest lecturer in Tongji. His research focuses on SHM, AI, BIM and structural analysis.
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