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Ulster University

Londonderry, Northern Ireland, United Kingdom

Digital Construction Analytics and BIM - MSc

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.

This stimulating course will develop your research and analytical skills, and provide you with advanced learning in digital transformation modelling and practices. You will explore Digital Construction Technologies, Management, Strategies; Building Information Modelling; and the fundamentals of Data Analytics.

Unlike other similar courses in the field, the key features of our course can be described by: the inclusion of Data Analytics modules; the strong link with industry to help you engage with project environments in order to provide digital solutions for real industry problems; and you will be also taught by published academics who will enhance your learning experience with research-led teaching. This MSc course provides an excellent foundation for further study, as well as a gateway to a wide range of employment opportunities.

Campus Information

Belfast Campus

Intakes

  • Jan
  • May
  • Sep

Application Processing Time in Days: 20

Application Process

More Information Required
10 Days
Possible Interview call from Institution
10 Days
Provisional / Unconditional Offer
10 Days
Visa Process
30 Days

Minimum English Language Requirements

English Level Description IELTS (1.0 -9.0) TOEFL IBT (0-120) TOEFL CBT (0-300) PTE (10-90)
Expert 9 120 297-300 86-90
Very Good 8.5 115-119 280-293 83-86
Very Good 8 110-114 270-280 79-83
Good 7.5 102-109 253-267 73-79
Good 7 94-101 240-253 65-73
Competent 6.5 79-93 213-233 58-65
Competent 6 60-78 170-210 50-58
Modest 5.5 46-59 133-210 43-50
Modest 5 35-45 107-133 36-43
Limited 4 32-34 97-103 30-36
Extremely Limited < 4 < 31 < 93 < 30

Job Opportunity Potential

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 special skills that the course will help learners to develop. These special skills become also essential for career progression. In addition to the construction related knowledge and skills obtained by studying this course, the Data Science knowledge and skills 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 course offers a unique opportunity for all Built Environment related graduates to study at Masters level and to develop skills applicable to their employment locally or internationally. The course strategy is designed to provide a balance between theory and practice with handson 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 skills to pursue a PhD route on graduation if they wish to.

PSW Opportunity

  • 2 Years PSW is applicable after completing a minimum duration of 9 months course (like- Undergraduate, Postgraduate Level)
  • 3 Years PSW is applicable after completing PhD level courses.

Admission Requirement / Eligibility Criteria

To be eligible to apply for a postgraduate degree course, you must provide evidence of competence in written and spoken English (GCSE grades A-C or equivalent); AND hold an Honours degree (2:2 or above) from a UK or Republic of Ireland or from the Council for National Academic Awards, the National Council for Educational Awards, the Higher Education and Training Awards Council, or from another institution which has been recognised by the Senate for this purpose.

Usually the minimum English language entry requirement is IELTS (academic) of 6.5 (with no band score of less than 6.0).