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  • DeadlineStudy Details:

    MSc 2 – 5 Years

Course Description

Embark on a career in a rapidly growing field and become a data scientist with an engineering background within a very lucrative field.

GCU’s MSc in Applied Data Science in Engineering will ensure you will become a competent specialist in Engineering Informed Data Science (EIDS) tools and technologies (or solutions) for high-value, highly complex assets. As part of this course, you will study a ground-breaking curriculum linked to industry digital engineering needs. You will learn to analyse complex systems and engineering assets, to deploy instrumentation as part of 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.

With both full-time and distance learning study available, the course was designed with input from industry for industry, and it was specifically constructed with a career development focus, so you will gain valuable skills you can immediately put to work in different industry sectors.

Apply your engineering domain knowledge to develop high-quality data science tools and solutions for physical systems (data scientists with an engineering background apply with their engineering knowledge to ensure higher quality of data).

Explore industry-standard commercial off-the-shelf solutions for system-level analysis and design of IIoT platforms and augmented reality enabled digital twins. Develop and apply predictive analytics to support data-informed engineering and business decisions.

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. Our goal is to deliver competent candidates ready to deliver value in the exciting journey of digital transformation.

Graduate opportunities 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 you 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 you graduate, you will be a competitive candidate for roles such as data analyst, data scientist, and data-enabled solutions designer for predictive capabilities targeted at complex assets.

You 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.

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

Entry Requirements

All entry requirements listed here should be used as a guide and represent the minimum required to be considered for entry. Applicants who are made a conditional offer of a place may be asked to achieve more than is stated. Entry Requirements UK honours degree 2:2 (or equivalent) in engineering (for example. mechanical, telecommunications and petroleum), physical sciences, and computer/IT engineering. We also welcome applicants with Industry qualifications/experience within the GCU Recognition of Prior Learning (RPL) Policy. English language Academic IELTS score of 6.0 (or equivalent) with no element below 5.5. Please note: if you are from a majority English speaking country, you may not be required to provide further proof of your English Language proficiency. Additional information Other academic and vocational qualifications

Each application to GCU is considered on an individual basis. If you do not have the typical academic entry qualifications, but can demonstrate relevant work experience and/or credits from recognised professional bodies, you may be eligible to enter this course via the University’s Recognition of Prior Learning scheme.

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Fees

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