MSc Applied Data Science in Engineering (16 Months)

Glasgow Caledonian University

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.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.