22/01/2021

26/01/2021

31/01/2022

2021 This programme services the increasing need for the application of data science methods to the Engineering and Built Environment sectors. To enable professionals to adapt to this rapidly changing context of the 4th Industrial Revolution, they need to understand and embrace the power of analytics and machine learning techniques to interpret, learn from, enrich, predict, and enhance how we design, construct, operate, maintain, and continuously improve our built and natural environments, and the systems, machines and equipment operating in them.

This programme will provide professionals from the Engineering and Construction domains with the skills to maximise the value of their data by analysing & interpreting this information to improve outcomes for industry, society, and individuals.

While the overall outcomes for each graduate from the programme will depend on the elective modules selected, successful completion of the Core Analytics Module Stack will ensure that a graduate will be able to:
o Critically appraise the capabilities and appropriate usage of a wide range of advanced analytics methods in engineering or built environment contexts;
o Critically evaluate the implementation of advanced analytics methods in engineering or built environment contexts;
o Select appropriate advanced analytics methods for engineering or built environment data sets and present insights to a variety of stakeholders to support decision-making.

2.2 in an engineering, built environment or related level 8 programme
or
equivalent knowledge as assessed via TU Dublin's (DIT's) Recognition of Prior Learning processes.

This programme services the increasing need for the application of data science methods to the Engineering and Built Environment sectors. To enable professionals to adapt to this rapidly changing context of the 4th Industrial Revolution, they need to understand and embrace the power of analytics and machine learning techniques to interpret, learn from, enrich, predict, and enhance how we design, construct, operate, maintain, and continuously improve our built and natural environments, and the systems, machines and equipment operating in them.

This programme will provide professionals from the Engineering and Construction domains with the skills to maximise the value of their data by analysing & interpreting this information to improve outcomes for industry, society, and individuals. Significant societal problems, such as addressing the shortage of adequate housing in Ireland and improving infrastructure worldwide, will only be successfully addressed by applying analytics techniques with advanced critical thinking by knowledgeable professionals.

This level 9 programme specifically targets the retention and career progression of staff through the development of new and valuable skills in the area of analytics, specifically for engineering and built environment, and with a particular focus on retaining and building a diverse workforce. The delivery mode of most of the programme enables flexibility through blended delivery, using asynchronous delivery and Open Educational Resources, with value-added face-to-face workshops and high intensity.

Content will mostly be delivered asynchronously (i.e. no requirement for simultaneous online access for lecturers and students) with synchronous delivery varying between evenings and mid-mornings by majority agreement with the class group.

Online and on the Bolton Street campus

Blended

Students will be required to own or have access to a laptop capable of running the software required for their chosen set of modules. Students who also take BIM-related modules will need equipment meeting current Autodesk standard specifications (Value spec: https://knowledge.autodesk.com/support/revit-products/learn-explore/caas/sfdcarticles/sfdcarticles/System-requirements-for-Autodesk-Revit-2021-products.html).

Lauren Brown

Rathdown House,
Room RD002,
Grangegorman Lower,
Dublin,
D07 X8R6

(01) 402 3445

springboard.city@tudublin.ie

RPL information is available at: https://tudublin.ie/study/part-time/how-to-apply/recognition-of-prior-learning/

Non-native English speakers will be required to produce evidence of their English capabilities according to TU Dublin's English Language Requirements policies: http://www.dit.ie/studyatdit/undergraduate/entryrequirements/englishlanguagerequirements/

In exceptional cases, English language assessments may be possible.

All applications must be made via this springboardcourses.ie website

All accompanying documentation must be submitted at the time of application. Failure to supply all required materials will disqualify candidates from consideration.

Please read all requirements carefully.

Programme handbook contain full information about the programme, its structure, options, outcomes, resources & facilities

https://sites.google.com/dit.ie/digitalconstengineeranalytics/home