We are living in a transformative age that is characterized by technological leaps in Artificial Intelligence (AI), data, connectivity and the Internet of Things (IoT). Maximizing the potential of such advances depends on a skilled workforce to drive and implement innovations. Yet this potential is constrained by the current skills gaps in embedded systems, IoT connectivity and AI. Flexible learning pathways, devised in close partnership with industry, provide a promising solution.
Academics at Anglia Ruskin University (ARU) in the United Kingdom have been looking at ways to expand and diversify the cohort of students entering computing. They have developed a suite of postgraduate courses that are based on micro credentials that are gained through distance learning. This flexible approach aims to make upskilling more accessible to a broad spectrum of students nationally and internationally. As part of the initiative, the ARU team worked with Arm Education to launch an Embedded Computing on Arm PG Cert. The professional certificate is based on Arm educational materials and delivered entirely online.
We find out about the strategic aims of the course and explore its industry-focused content with ARU’s Head of School of Computing and Information Science, Professor Marcian Cirstea, and Course Leader, Dr Oliver Faust.
“Arm is creating a sustainable ecosystem that can enable better progress and more benefits for the university – for the students in particular – but also for staff involved in research.”
Professor Marcian Cirstea, Head of the School of Computing and Information Science at Anglia Ruskin University.
At ARU, the focus is on ensuring that students gain relevant, hands-on skills that meet industry’s need for qualified talent to support technological growth. The pioneering Embedded Computing on Arm PG Cert acts as a standalone qualification or a seamless gateway to further studies, for example ARU’s Embedded Computing and Machine Learning MSc.
The flexibility provided by the distance learning and micro credential model is designed to attract students from different backgrounds, for example professionals wishing to update their skills or recent graduates wanting to specialize in embedded computing. The course also furthers the aims of the Semiconductor Education Alliance, an ecosystem of leading industry and academic partners who are working to tackle the semiconductor talent shortage.
According to Professor Cirstea, “We want our students to be exposed to what they really need to know, to develop the skills that are needed in the industry. When they go into employment, they will have a strong set of technical skills, as well as a set of soft skills that will enable them to perform well.”
“Arm is developing products at the core of what is used everywhere nowadays, many companies are making use of its products. They are forward-looking on key aspects of embedded computing and the use of AI and machine learning. This is what enables progress, the further optimization of products, and gets products to market faster. We see Arm at the forefront of these developments, and it made a lot of sense for us to engage with them strongly.”
“We have valued and used Arm materials over the years to understand their products, which we use in practical modules. In discussions with Arm Education, we discovered that there is a lot more educational content available. These materials are now embedded in this course. We added the aspects that are more academic, that build up towards an assessed project.”
“Arm was able to provide us with materials that are clearly linked to the products that they offer, to the hardware and software that’s currently used in industry. This enabled the course to be developed with a much higher confidence that what the students are getting is very close to industry needs, and Arm can be confident that students are exposed to what their engineers think it's important for them to know.”
“The Semiconductor Education Alliance is a great initiative that brings us together with other institutions. Arm is creating a sustainable ecosystem that can enable better progress and more benefits for the university – for the students in particular – but also for staff involved in research.”
This course is cutting-edge. It's not only about employability, but also about creating opportunity and creating commercial ventures.”
Dr. Oliver Faust, Course Leader, Embedded Computing on Arm PG Cert and Embedded Computing and Machine Learning MSc.
The Embedded Computing on Arm PG Cert is composed of two modules. The first, Embedded Systems Essentials with Arm, enables students to understand embedded computing and how combining hardware and software skills can support the development of advanced applications. The second, Internet of Things (IoT) and Machine Learning at the Edge on Arm, explores how sophisticated intelligent systems can be achieved on local hardware, and improve the speed, security, and efficiency of future computing.
Dr. Oliver Faust, Course Leader, Embedded Computing on Arm PG Cert and Embedded Computing and Machine Learning MSc says “Hardware and software are the two big drivers, not only behind this course, but also behind the progress of humankind. In the first module we do the basics, the fundamentals of embedded systems so that students get familiar with this ecosystem – it's not an environment, it's a whole ecosystem that Arm has built.”
“The second module covers the IoT and machine learning on the Edge, this refers to the ‘edge’ of a network, on a device or sensor, for example. In the past, the pendulum swung towards cloud servers doing the heavy lifting and processing. With Artificial Intelligence (AI) we want to swing it back towards the Edge, so we make decisions on the device itself instead of somewhere in the cloud, where there are latency and security concerns.” “This course is cutting-edge. It's not only about employability, but also about creating opportunity and creating commercial ventures.”
“The second module covers the IoT and machine learning on the Edge, this refers to the ‘edge’ of a network, on a device or sensor, for example. In the past, the pendulum swung towards cloud servers doing the heavy lifting and processing. With Artificial Intelligence (AI) we want to swing it back towards the Edge, so we make decisions on the device itself instead of somewhere in the cloud, where there are latency and security concerns.”
“This course is cutting-edge. It's not only about employability, but also about creating opportunity and creating commercial ventures.”
It is a sentiment shared by Professor Cirstea, who concludes: “The partnership with Arm doesn’t just entice students; it excites them. They don’t just see a dry algorithm, they see the light at the end of the tunnel, the architecture of a company that will be found in so many products, devices and applications of the future.”
For further details on Anglia Ruskin’s online postgraduate certificate on Embedded Computing on Arm.
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