| Program start date | Application deadline |
| 2025-09-01 | - |
Program Overview
Digital Construction Analytics and BIM - MSc
Overview
Digital Construction at Ulster is an industry-linked highly creative course, specialising in BIM, Digital Technologies and Data Analytics.
Summary
This MSc in Digital Construction is the perfect course if you are passionate about discovering how the advanced digital technologies and BIM have transformed AEC industry, and understanding how Data Analytics can improve the management of construction projects.
About this course
In this section
- About
- Attendance
- Start dates
- Teaching, Learning and Assessment
- Academic profile
About
Digital platforms enable greater connectivity of construction processes to accomplish sustainable projects by simulating, predicting, optimising, managing and monitoring various UN Sustainable Development Goals within the AEC industries especially with the vision towards connecting the real and digital worlds.
Our MSc course is designed to introduce you to the essential areas of digital construction concepts, technologies, BIM and Data Analytics that will help you develop your career while deepening and widening your understanding of the digital environment that the industry operates nowadays.
This Ulster University MSc is a joint course between the Belfast School of Architecture & Built Environment and the School of Computing, Engineering & Intelligent Systems designed to meet the needs of experienced or aspiring professionals who wish to expand their knowledge and skills to equip them for the challenges facing the AEC industry.
By joining this Ulster University MSc in Digital Construction you will be joining a group of diverse professionals who come from all over the world to study with us. You will expose yourself to different cultures and develop an international network of professionals.
At Ulster University we put a particular emphasis on equipping students with the theoretical, practical knowledge and expertise needed to apply their learning from the Masters. You will engage with project environments in order to provide digital solutions for real industry problems. We also invite leading industry professionals to deliver guest lectures to MSc students.
Attendance
The course is based on a modular structure with three modules in each semester. Attendance is a mix of class-based, computer-lab, and group work. For full time students, nine hours of staff contact time per week and 36 hours self-directed study per week (all on average).
The modules in Semester 1 will enable you to obtain fundamental knowledge on the subjects of Digital Construction, BIM and Data Analytics. In Semester 2, you will obtain in-depth knowledge on Data Analytics and develop expertise in applying your knowledge on Digital Construction in a project-based environment. In Semester 3, you will work on a specific research topic to advance your research skills and explore new areas in the field of Digital Construction.
Over the duration of the course you will develop your knowledge of the technical, theoretical and practical contexts which have led to the evolution of a dynamic and innovative digital construction industry.
Start dates
- September 2025
Teaching, Learning and Assessment
We aim to provide a learning and teaching environment where innovation and discovery are central to your education and in which you can take pride that you are an Ulster graduate. Many of the modules are research informed, where you can gain hands-on experience in contemporary research laboratories alongside current research projects. There will be an emphasis on challenge and collaboration, exploring new concepts and real-world construction problems. This will help you to be creative in solution thinking, both individually and cooperatively, so you can develop your own and other’s employable skills.
Teaching is delivered primarily through lectures, computer-labs, group work, and presentations from industry professionals. Project-driven and enquiry-based approaches to learning are central to the course, which includes practical challenges, real-world case studies, team-driven assessments/presentations and industry projects. The use of digital technologies will enrich our learning and teaching environment. Learning and teaching on the course makes use of a suite of Digital Learning tools to create a learning community within Virtual Learning Environment (Blackboard Learn) and Common Data Environments for construction industry. These will support all course modes of delivery (including Distance Learning) and host module areas complete with learning materials of varied media and interactive tools for student engagement, communication and collaboration, online assessment and feedback and content delivery offering you the flexibility to study at your own pace, any place and time.
A range of assessment techniques will be used to enable you to demonstrate your knowledge and understanding of the course concepts and content but also to enable interaction with your peers and the course team. These will include Blogs, chats, on-line forums, Essays and reports, presentations and simulations, and Peer review. The course is assessed in a number of ways to allow us to provide you with valuable feedback on your progress. These mainly include coursework and class tests. All assessments will have clearly identified marking criteria and you will be provided with clear briefs.
The course is designed to cover topics that address key industry challenges within the themes of Digital Construction from the view of addressing global as well as local challenges, thereby ensures students are global citizens. You are expected to apply the obtained Data Science knowledge in the field of Digital Construction; for example, to develop solutions for challenges of: Lean Construction to reduce waste, Generative Design to achieve Net-Zero emission, product innovation, whole life asset performance, evaluating new relevant technologies (e.g. off-site manufacturing), and achieving energy efficient construction. Example of design challenges within Computing modules include: big data processing, data visualisation dashboards and dealing with bias in machine learning applications. Mini-project-based or design-challenge assessment methods are also used throughout the course to also embed a sustainability focus where students develop solutions for low-impact computing and data innovation to ensure the sustainable or viability of business critical systems.
Academic profile
Teaching is informed by academic research at Belfast School of Architecture and Built Environment. The Built Environment (Construction Eng. & Mgmt) programme at Ulster ranked 4th out of 54 programmes in the UK Building League Table in the last two Complete University Guide (2021 & 2022). The Built Environment programme team members at Ulster University have a strong track record in the area of BIM and Digital Construction research, publishing widely in the area since 2013, and supervising Knowledge Transfer Partnerships with industry on Digital Twins. The Computing, Engineering, Intelligent Systems team are active researchers within the Cognitive Analytics Research Lab (CARL). The contribution of Ulster team to Digital Construction and BIM research in Ireland between the period 2016 – 2020 has been acknowledged in a recent publication at CITA BIM Gathering (2021) that conclude “The most prolific academics in publishing in digital construction appear to be Comiskey and McKane in the area of technology, data sharing and education; Motawa in big data and building performance…”. The novel work in this area was recognised by Ulster University who awarded the team a prestigious Distinguised Teaching Fellowship Award in 2016. The team involved in this area have supervised and supported students in various national/international research events, e.g. a student has recently won a prestigious CIAT International Award.
The University employs over 1,000 suitably qualified and experienced academic staff - 60% have PhDs in their subject field and many have professional body recognition.
Courses are taught by staff who are Professors (19%), Readers, Senior Lecturers (22%) or Lecturers (57%).
We require most academic staff to be qualified to teach in higher education: 82% hold either Postgraduate Certificates in Higher Education Practice or higher. Most academic and learning support staff (85%) are recognised as fellows of the Higher Education Academy (HEA) by Advance HE - the university sector professional body for teaching and learning. Many academic and technical staff hold other professional body designations related to their subject or scholarly practice.
The profiles of many academic staff can be found on the University’s departmental websites and give a detailed insight into the range of staffing and expertise. The precise staffing for a course will depend on the department(s) involved and the availability and management of staff. This is subject to change annually and is confirmed in the timetable issued at the start of the course.
Occasionally, teaching may be supplemented by suitably qualified part-time staff (usually qualified researchers) and specialist guest lecturers. In these cases, all staff are inducted, mostly through our staff development programme ‘First Steps to Teaching’. In some cases, usually for provision in one of our out-centres, Recognised University Teachers are involved, supported by the University in suitable professional development for teaching.
Modules
Here is a guide to the subjects studied on this course.
Courses are continually reviewed to take advantage of new teaching approaches and developments in research, industry and the professions. Please be aware that modules may change for your year of entry. The exact modules available and their order may vary depending on course updates, staff availability, timetabling and student demand. Please contact the course team for the most up to date module list.
Year one
Digital Construction: Technology, Strategy & Management
Year: 1
Status: C
This module explores the area of Digital Construction, both in general, and as a means of helping to address pertinent AECFM sector problems or processes identified as requiring advancement. Learners will study contemporary practice and undertake their own research for an identified task. Additionally, there will be a focus on strategic and management capabilities. This module will provide connections to other related subject fields for learners to develop a holistic view of the opportunities resulting from the integration of digital construction processes and/or technologies. The module aims to close the gap in the curricula for supporting the AECFM sector in embracing the Industry 4.0 vision.
Business Intelligence and Analytics
Year: 1
Status: C
This module aims to contextualise the role of Business Intelligence and Business Analytics and why we need them. A particular focus will be on how to turn already stored data into valuable information and why this is important. For instance, vast amounts of data regarding company's customers and operations is routinely collected and stored in large corporate data warehouses. This data can be of immense value if properly analysed. Students will explore techniques and tools for data analysis, and presentation of the results to non-technical and managerial staff, in alignment with business strategies. Business intelligence and analytics however, are open to certain ethical and consent issues along with risks. These will be analysed, reviewed and evaluated.
Introduction to Data Science
Year: 1
Status: C
This module serves as an entry point into the exciting field of data science, specifically tailored for individuals with no prior programming or data science experience. Throughout the course, students will acquire a strong foundation in fundamental concepts and techniques essential to data science. Key areas covered include data collection, processing, analysis, and visualisation. Additionally, students will receive an introduction to the fundamental principles of computer programming within data science. This encompasses understanding syntax, data structures, programming terminology, techniques, libraries, and core concepts. By the end of this module, students will have developed proficiency in core data science techniques, blending theoretical learning with practical exercises using a common data science programming language.
Year two
Building Information Modelling
Year: 2
Status: C
The aim of this module is to provide students with insight into the main concepts and principles of Building Information Modelling/Management, vis-à-vis processes, protocols, and enabling technologies. The module is mainly concerned with recent paradigm shift within the AECFM industries worldwide to implement BIM in projects. This module is also heavily inspired by the prospective of UK BIM Framework (formerly BIM level 3) and the relevant BIM BS ISO standards. The module will cover strengths and weaknesses, opportunities and threats associated with adopting BIM in AECFM projects and its impact on working procedures as well as business models of AECFM industry. This will be further elaborated in lights of real-life national and international scenarios and case studies.
Industry Project
Year: 2
Status: C
This module is industry focused where students will work collaboratively in teams to develop solutions for specific projects normally within an industrial or practice-based test bed, and/or in association with an appropriate design or industrial organisation. Field trips and regular progress reports are an important aspect of the module. The module is designed to cover topics that address key industry challenges within the themes of Digital Construction. Students are expected to apply the obtained Data Science knowledge in the field of Digital Construction; for example, to develop solutions for challenges of: Lean Construction to reduce waste, Generative Design to achieve Net-Zero emission, product innovation, whole life asset performance, evaluating new relevant technologies (e.g. off-site manufacturing), and achieving energy efficient construction.
Research Design and Dissertation
Year: 2
Status: C
This module enables the student to undertake an independent in-depth study of a particular aspect of Construction Management. It facilitates development of skills in problem solving and decision making whilst also refining other skills including investigative and evaluative skills. Students are required to demonstrate their knowledge of the subject researched, skills in critical analysis and use of investigative methods. Students are required to display these skills in written and oral format that will clearly display analysis of the principal arguments and conclusions of their work.
Data Validation and Visualisation
Year: 2
Status: C
High-quality data is the precondition for analysing and using big data and for guaranteeing the value of the data. This module, introduces the data quality challenges faced by big data. It will present tools and techniques employed to ensure data quality from data collection and computational procedures to facilitate automatic or semi-automatic identification and elimination of errors in large datasets. The module also introduces the topic of understanding and interpreting data through descriptive statistical methods. This will be achieved through a range of techniques such as Statistical metrics, Univariate analysis and Multivariate analysis. Students will develop the knowledge to assess the quality of the data and the skills necessary to perform appropriate data cleaning operations. In addition, students will have an understanding of processing data and interpreting and visualising results.
Research Methods and Project
Status: O
Year: 2
This module is optional
This module provides students with a broad understanding of research methods and techniques, and how these can be used to investigate a research problem in any context. Students will be provided with the necessary theoretical foundations in statistical research, including the ability to plan research ethically and conduct a literature review. Students will also be able to record, analyse, interpret and present qualitative and quantitative data appropriately.
Standard entry conditions
We recognise a range of qualifications for admission to our courses. In addition to the specific entry conditions for this course you must also meet the University’s General Entrance Requirements.
In this section
- Entry Requirements
- English Language Requirements
Entry Requirements
At least 2:2 Honours degree (or equivalent) in Architecture, Engineering, Construction or other Built Environment related subject. Previous computer programming skills are not essential requirement. Applicants from other relevant backgrounds (e.g. Data Science and Computer Game) can be considered. Applicants must also provide evidence of English Qualification to the level that meets the University requirements.
English Language Requirements
English language requirements for international applicants
The minimum requirement for this course is Academic IELTS 6.0 with no band score less than 5.5. Trinity ISE: Pass at level III also meets this requirement for Tier 4 visa purposes.
Ulster recognises a number of other English language tests and comparable IELTS equivalent scores.
- English language requirements
- Your country
Careers & opportunities
In this section
- Career options
Career options
The area of Digital Construction and BIM is expanding in the market and new posts have been created recently in the industry (e.g. BIM Manager, Information Manager) which need expertise that the course will help learners to develop. This expertise will be essential for career progression. In addition to the construction related knowledge and skills obtained by studying this course, the Data Science knowledge and expertise will reinforce the graduates’ abilities and capabilities; hence support their employability in relation to Information Management roles that become more mainstream in the industry. The programme offers a unique opportunity for all Built Environment related graduates to study at Masters level and to develop expertise applicable to their employment locally or internationally. The programme strategy is designed to provide a balance between theory and practice with a hands on approach on solving real industry problems in collaboration with industry partners. This strategy will provide graduates with key critical thinking and analysis skills that are transferrable and applicable across a wide range of industry sectors. Graduates will be also equipped with the essential expertise to pursue a PhD route on graduation if they wish to.
Fees and funding
10% Alumni Discount
Are you a graduate of Ulster University? Did you know you could be eligible for a 10% fees discount.
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Tuition Fee Loans Available
Students domiciled in Northern Ireland, Republic of Ireland and UK students can apply to Student Finance NI for a Tuition Fee loan of up to £6,500 (subject to eligibility).
The price of your overall programme will be determined by the number of credit points that you initiate in the relevant academic year.
For modules commenced in the academic year 2025/26, the following fees apply:
Fees Credit Points| NI/ROI/GB Cost| International Cost*
---|---|---
5 | £201.10| £494.70
10 | £402.20| £989.40
15 | £603.30| £1,484.10
20 | £804.40| £1,978.80
30 | £1,206.60| £2,968.20
60 | £2,413.20| £5,936.40
120 | £4,826.40| £11,872.80
180 | £7,239.60| £17,809.20
240| £9,652.80| £23,745.60
NB: A standard full-time PGCert is equivalent to 60 credit points per year. A standard full-time PGDip is equivalent to 120 credit points per year.
*International student access to courses is subject to meeting visa requirements. More information can be found in the Visas and Immigration section.
Annual Increase Disclaimer
Important Notice: Annual Fees Increase
Annual Fees Increase Disclaimer
Fees illustrated are based on academic year 25/26 entry and are subject to an annual increase.
If your study continues into future academic years your fees are subject to an annual increase. Please take this into consideration when you estimate your total fees for a degree.
Additional mandatory costs are highlighted where they are known in advance. There are other costs associated with university study.
Visit our Fees pages for full details of fees.
Correct at the time of publishing. Terms and conditions apply.
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Additional mandatory costs
It is important to remember that costs associated with accommodation, travel (including car parking charges) and normal living will need to be covered in addition to tuition fees.
Where a course has additional mandatory expenses (in addition to tuition fees) we make every effort to highlight them above. We aim to provide students with the learning materials needed to support their studies. Our libraries are a valuable resource with an extensive collection of books and journals, as well as first-class facilities and IT equipment. Computer suites and free Wi-Fi are also available on each of the campuses.
There are additional fees for graduation ceremonies, examination resits and library fines.
Students choosing a period of paid work placement or study abroad as a part of their course should be aware that there may be additional travel and living costs, as well as tuition fees.
See the tuition fees on our student guide for most up to date costs.
