12 monthsProgramme duration
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
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 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.
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.
This master's degree course is accredited by the Institute of Measurement and Control (InstMC) and the Institution of Engineering and Technology (IET) on behalf of the Engineering Council as meeting the requirements for further learning for registration as a Chartered Engineer. Please note, you must hold a CEng accredited BEng/BSc (Hons) undergraduate degree, as well as the MSc, in order to comply with full CEng registration requirements.
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 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.
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 their engineering knowledge to ensure a 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.
This master's degree course is accredited by the Institute of Measurement and Control (InstMC) and the Institution of Engineering and Technology (IET) on behalf of the Engineering Council as meeting the requirements for further learning for registration as a Chartered Engineer. Please note, you must hold a CEng accredited BEng/BSc (Hons) undergraduate degree, as well as the MSc, in order to comply with full CEng registration requirements.
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
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 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.
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.
This master's degree course is accredited by the Institute of Measurement and Control (InstMC) and the Institution of Engineering and Technology (IET) on behalf of the Engineering Council as meeting the requirements for further learning for registration as a Chartered Engineer. Please note, you must hold a CEng accredited BEng/BSc (Hons) undergraduate degree, as well as the MSc, in order to comply with full CEng registration requirements.
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 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.
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 their engineering knowledge to ensure a 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.
This master's degree course is accredited by the Institute of Measurement and Control (InstMC) and the Institution of Engineering and Technology (IET) on behalf of the Engineering Council as meeting the requirements for further learning for registration as a Chartered Engineer. Please note, you must hold a CEng accredited BEng/BSc (Hons) undergraduate degree, as well as the MSc, in order to comply with full CEng registration requirements.
Admission Requirements
Relevant experience (Recognition of Prior Learning)
GCU's flexible entry policies exist to allow relevant work experience and prior learning to be considered towards standard entry or advanced entry into a course.
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 (RPL) scheme.
Minimum entry requirements
Minimum entry requirements are for widening access students only. If you are from a group that is not currently well-represented in higher education you may qualify as a widening access student. This includes living in a target postcode area, attending a target school or college, attending SWAP, are care-experienced or provide care for someone else, have refugee status or are an asylum seeker.
GCU's flexible entry policies exist to allow relevant work experience and prior learning to be considered towards standard entry or advanced entry into a course.
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 (RPL) scheme.
Minimum entry requirements
Minimum entry requirements are for widening access students only. If you are from a group that is not currently well-represented in higher education you may qualify as a widening access student. This includes living in a target postcode area, attending a target school or college, attending SWAP, are care-experienced or provide care for someone else, have refugee status or are an asylum seeker.
1 Year
- Candidates are required to submit references or letter(s) of recommendation for acceptance
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