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Master of Science - Engineering - Applied Data Science

GCU’s MSc in Applied Data Science in Engineering will ensure students will become competent specialists in Engineering Informed Data Science (EIDS) tools and technologies (or solutions) for high-value, highly complex assets. As part of this course, students will study a ground-breaking curriculum linked to industry digital engineering needs. They will learn to analyse complex systems and engineering assets, to deploy instrumentation as part of Industrial Internet of Things (IIoT) architectures, to store, manipulate and analyse big data effectively by implementing data visualisation techniques and producing digital twins capable of transforming data into actionable insights supporting informed engineering/business decisions.

The course was designed with input from industry for industry, and it was specifically constructed with a career development focus, so students will gain valuable skills they can immediately put to work in different industry sectors.

Students will have the opportunity to apply their engineering domain knowledge to develop high-quality data science tools and solutions for physical systems. Data scientists with an engineering background apply their engineering knowledge to ensure a higher quality of data. They will also explore industry-standard commercial off-the-shelf solutions for system-level analysis and design of IIoT platforms and augmented-reality-enabled digital twins. Students will also develop and apply predictive analytics to support data-informed engineering and business decisions. Finally, they will learn how to develop data visualisation dashboards to maximize the level of engineering insights related to asset performance, health management, operations, maintainability and through-life engineering support solutions.

The course requirements were captured via in-depth interviews with representatives of Scottish engineering firms (part of global engineering organisations) and the taught modules were designed to fulfil a real need in terms of digital engineering skills. Input from engineering institutes and governmental bodies was also captured to ensure the relevance of the curriculum in the context of digitalisation of assets’ design, manufacturing, operations, and through-life engineering support of complex systems. GSU's goal is to deliver competent candidates ready to deliver value in the exciting journey of digital transformation.

The MSc Applied Data Science in Engineering offers graduates a highly focused skillset that is valuable to an extremely wide range of industry sectors currently going through the digital transformation process.

Across these industries graduates might focus on predictive analytics for asset performance, on solutions to increase uptime and decrease downtime, the use of instrumentation, big data, optimisation and engineering-informed analytics via digital twins, on digital readiness or enhance decisions related to design, operations, or maintenance via data analytics. When they graduate, students will be competitive candidates for roles such as data analyst, data scientist, and data-enabled solutions designer for predictive capabilities targeted at complex assets.

Graduates might also want to pursue a career as a digital change leader for an engineering organisation bridging the knowledge gap between subject matter experts and domain knowledge, data scientists, data engineers and architects, IT/OT specialists and business owners.

Graduates can also use the course as a foundational knowledge base for PhD studies in the Applied Data Science or Data-Enabled Industrial Engineering fields.

Requirements

Listed below are the documents required to apply for this course.

4-Year Bachelor's Degree

70.0 %

Total: 6.0

Reading

5.5

Writing

5.5

Listening

5.5

Speaking

5.5

Total: 78.0

Reading

18.0

Writing

17.0

Listening

17.0

Speaking

20.0

Total: 59.0

Reading

59.0

Writing

59.0

Listening

59.0

Speaking

59.0

This program offers conditional admissions For conditional admission, you are required to provide English proficiency scores: Min TOEFL iBT: 35 Min Listening: 3, Min Reading: 3, Min Speaking: 12, Min Writing: 12 Min IELTS overall: 5 Min Listening: 4.5, Min Reading: 4.5, Min Speaking: 4.5, Min Writing: 4.5

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  • Sep 2025
  • Sep 2026