Master´s Degree Programme in Computing in Construction (in English): Computing in Construction
Code: T2425S6
- Degree title
- Master of Engineering, MEng
- Credits
- 60 ects
- Duration
- 1.5 years (60 ECTS)
- Start semester
- Autumn 2025
- Teaching language
- English
Descriptions
The objective of the Computing in Construction programme is to create competencies for software development in the real estate and construction sector. Students will learn how to programmatically create, enrich, link and process the various kinds of models and data produced in the construction industry, and create software solutions to address practical challenges faced during the construction lifecycle. They develop their skills in software development projects and gain skills to lead them.
Digitalisation of construction is closely connected to the goals of sustainable development. In this programme, the challenges of construction and their digital solutions are approached from a life cycle perspective. Ecological sustainability is supported through life cycle assessment and life cycle-based energy analysis and carbon footprint and handprint calculation. Information content that supports the recycling of construction parts and materials plays a significant role in minimising harmful environmental effects and the use of virgin raw materials. Economic sustainability is promoted by optimising the life cycle costs of design proposals. In terms of the productivity development of construction projects, the interoperability of digital systems and the automation of information sharing are essential. To support social sustainability, the studies include digital solutions to improve the occupants’ safety and comfort and to increase the social interaction between stakeholders. An important goal of information management in construction is to support the distributed ownership and responsibility typical in construction projects and built environments.
The larger mission of the programme is to improve productivity in the real estate and construction sector by creating, enhancing, and integrating information flows, as well as by promoting intelligent data processing and utilisation throughout the entire construction lifecycle. The students will gain expertise in smart technologies, artificial intelligence solutions, climate impact, and circular economy to address challenges in new construction, renovation, and reconstruction, as well as in the operational and decommissioning phases of buildings. The focus is on the creation of a healthy and safe built environment where people can live comfortably and conveniently at all stages of life.
The programme is targeted to professionals in working life who want to understand and to develop practical skills to work on data and models in the real estate and construction domain, and who want to work on software development to increase the quality, sustainability, interoperability, productivity, and information security in the construction sector. The prerequisite for participation is a bachelor's degree in engineering and at least two subsequent years of work experience. To be selected as a student, basic computer programming and software development skills are required.
The programme consists of Professional Studies (30 ECTS) and Master’s Thesis (30 ECTS). The Professional Studies consist of common studies (20 ECTS) supplemented by optional studies and elective studies (5 ECTS each). The planned duration of the programme is one and a half years but if necessary, studies can be completed in one year.
Development
The contents of the programme have been developed in collaboration with the software industry specialised in construction domain, professional associations for real estate and construction, and innovative construction companies with software development interests. The continuing relevance of the content is ensured through a steering group formed from these stakeholder groups.
Further information
Unit: Myllypuro, Myllypurontie 1, Helsinki
Head of School: Jorma Säteri
Head of Degree Programme: Seppo Törmä
Administrator: Minna Passi
Objective
The student has software development competencies to address the challenges faced in real estate and construction domain.
In particular, the student
• is familiar with the variety of data formats for building models, city models, and technical networks, as well as for sensor and condition data generated by building automation systems and IoT systems
• understands how to access, process and interlink the varieties of data and models in the real estate and construction industry
• has practical skills to apply, develop and implement modern computational methods and tools to process the data with the purpose of increased quality, sustainability, productivity, and security of construction
• can use advanced software tools to process and manage the data
• develops skills needed in software development projects and gains skills to lead such projects.
Select timing, structure or classification view
Show study timings by semester, study year or period
| Code | Name | Credits (ECTS) | 2025-2026 | 2026-2027 | Autumn 2025 | Spring 2026 | Autumn 2026 | 1. / 2025 | 2. / 2025 | 3. / 2026 | 4. / 2026 | 1. / 2026 | 2. / 2026 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| T2425S6-1001 |
Advanced Professional Studies
(Choose all ) |
20 | |||||||||||
| TX00FE95 | Computational Representations of Built Environments | 5 | |||||||||||
| TX00FE96 | Data Gathering over Construction Lifecycle | 5 | |||||||||||
| TX00FE97 | Managing and Sharing Construction Data | 5 | |||||||||||
| TX00FF00 | Digital Twins in Construction | 5 | |||||||||||
| T2425S6-1002 |
Optional Studies
(Choose ects: 5) |
5 | |||||||||||
| TX00FE99 | Computational Design and Optimisation | 5 | |||||||||||
| TX00FX22 | Artificial Intelligence in Construction | 5 | |||||||||||
| T2425S6-1003 |
Elective Studies
(Choose ects: 5) |
5 | |||||||||||
| T2425S6-1007 |
Master's Thesis
(Choose all ) |
30 | |||||||||||
| XX00FB87 | Master’s Thesis | 30 | |||||||||||
| Total | 60 | 30 | 0 | 15 | 15 | 0 | 7.5 | 7.5 | 7.5 | 7.5 | 0 | 0 |
Due to the timing of optional and elective courses, credit accumulation per semester / academic year may vary.
STRUCTURE Master (A18.12.2014/1129)
Asetuksen 18.12.2014/1129 mukainen rakenne. 2 § Opintojen rakenne Ylempään ammattikorkeakoulututkintoon johtaviin opintoihin kuuluu: 1) syventäviä ammattiopintoja; 2) vapaasti valittavia opintoja; 3) opinnäytetyö.
| Master´s Thesis |
| Master’s Thesis |
| Advanced Professional Studies |
| Computational Representations of Built Environments |
| Data Gathering over Construction Lifecycle |
| Managing and Sharing Construction Data |
| Digital Twins in Construction |
| Computational Design and Optimisation |
| Artificial Intelligence in Construction |
| Elective Studies |
|
No attached course units |
| Not grouped |
ARENE 2022::UAS shared competences::Master’s degree
Replaces the “Metropolia's Generic Competences::Master's Degree” -matrix. Heidi Rontu/31.8.2022
|
Ethics
The graduating student assesses and promotes the realisation of ethical principles and values of their field of profession, taking equality and non-discrimination into account. |
| Managing and Sharing Construction Data |
| Digital Twins in Construction |
| Artificial Intelligence in Construction |
|
Proactive development
The graduating student is able to manage the development of new solutions that anticipate the future and produces new information using different research and development methods. |
| Computational Representations of Built Environments |
| Data Gathering over Construction Lifecycle |
| Managing and Sharing Construction Data |
| Digital Twins in Construction |
| Computational Design and Optimisation |
| Artificial Intelligence in Construction |
|
Internationality and multiculturalism
The graduating student is able to develop and manage multicultural and international operating environments and networks. |
| Computational Representations of Built Environments |
| Data Gathering over Construction Lifecycle |
| Managing and Sharing Construction Data |
|
Sustainable development
The graduating student develops and manages sustainable and responsible operating methods in their work and promotes sustainable change in their work community and society. |
| Computational Representations of Built Environments |
| Data Gathering over Construction Lifecycle |
| Managing and Sharing Construction Data |
| Digital Twins in Construction |
| Computational Design and Optimisation |
|
Learning to learn
The graduating student promotes their own and their community's continuous learning and competence development, drawing on knowledge from different fields and the opportunities of digitalisation. |
| Computational Representations of Built Environments |
| Data Gathering over Construction Lifecycle |
| Managing and Sharing Construction Data |
| Digital Twins in Construction |
| Computational Design and Optimisation |
| Artificial Intelligence in Construction |
|
Operating in a workplace
The graduating student is able to develop and manage their work community and reforms working life. - Is able to develop and manage multidisciplinary teams and work communities. |
|
No attached course units |
| Not grouped |
| Master’s Thesis |
| Code | Name | Credits (ECTS) |
|---|---|---|
| T2425S6-1001 |
Advanced Professional Studies
(Choose all ) |
20 |
| TX00FE95 | Computational Representations of Built Environments | 5 |
| TX00FE96 | Data Gathering over Construction Lifecycle | 5 |
| TX00FE97 | Managing and Sharing Construction Data | 5 |
| TX00FF00 | Digital Twins in Construction | 5 |
| T2425S6-1002 |
Optional Studies
(Choose ects: 5 ) |
5 |
| TX00FE99 | Computational Design and Optimisation | 5 |
| TX00FX22 | Artificial Intelligence in Construction | 5 |
| T2425S6-1003 |
Elective Studies
(Choose ects: 5 ) |
5 |
| T2425S6-1007 |
Master's Thesis
(Choose all ) |
30 |
| XX00FB87 | Master’s Thesis | 30 |