Embedded Computing and Machine Learning

Program Overview

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MSc Embedded Computing and Machine Learning

Introduction

Advance your career in embedded systems and artificial intelligence (AI) with our 100% online Master’s degree in Embedded Computing and Machine Learning. Enhance your understanding of embedded systems and artificial intelligence (AI) with our Master’s degree in Embedded Computing and Machine Learning. Study part-time by distance learning and develop the skills you need to harness the power of machine learning applications in various industrial contexts.

Our Embedded Computing and Machine Learning MSc will give you the opportunity to explore the industry trends where big chip designing and manufacturing multinational companies are emphasising embedded and portable devices optimised for machine learning at the edge.

During the first two modules, you'll gain skills to leverage Arm technologies and develop intelligent, distributed, heterogeneous, and secure solutions. You'll also expand your knowledge and skills in advanced topics of machine learning and AI, such as deep learning, generative AI and their applications to prompt engineering.

You'll crown your work on this course with a final year project which provides you with a platform to showcase the acquired skills and knowledge in an application domain of interest.

Embedded computing, especially when paired with machine learning, promises to provide the tools to enhance technology, business models and decision-making across a range of sectors, from industrial automation, quality control, manufacturing, transport, banking and cyber security to health and social care.

By working on real-life case studies with industry tools, you'll become proficient in embedded systems tools and techniques for machine learning on the edge applications for industry and apply your hardware and software skills in a major project utilizing advanced machine learning techniques.

In addition to the tuition fees, you will also need to purchase some hardware, such as ST DISCO-L475E, and sensors, which we do not expect to exceed £100. You will also need access to a fairly modern laptop or personal computer which runs Microsoft Windows 10 or later. Furthermore, admin rights are required to install relevant software packages.

You may also be interested in our online Embedded Computing on Arm PG Cert, or these modules may be taken on a module-by-module basis. Contact us for further details.

Course Options

• 3 years part-time
• September
• Distance learning

Key Facts

• STUDY OPTIONS: 3 years part-time
• START DATES: September
• LOCATION: Distance learning
• FEE (UK AND EU STUDENTS): £8,200 Distance learning students starting 2024/25 (total cost)

Teaching and Assessment

Our MSc in Embedded Computing and Machine Learning is strategically designed to immerse you in the dynamic realm of embedded systems.

You’ll be introduced to the core principles of embedded systems, with a specific emphasis, in the first two modules, on industry-relevant educational materials developed in partnership with Arm. This serves as the gateway to comprehending the intricacies of Arm technology, a crucial skill set for anyone aspiring to thrive in the embedded computing domain.

Moving forward, the course delves into the intersection of Internet of Things (IoT) and machine learning, offering you a profound insight into the potential of these technologies when implemented at the edge. You’ll gain a unique perspective on how IoT and machine learning synergize to create innovative solutions.

You'll be further exposed to machine learning techniques, emphasising their application in embedded systems. As the demand for machine learning expertise in embedded computing grows, this ensures that you’ll be well-versed in the latest techniques, setting you apart in the competitive job market.

The course takes you to the forefront of generative artificial intelligence, providing a deep understanding of prompt engineering and its applications in embedded computing. It will equip you with the skills to prompt AI systems effectively, enabling you to generate tailored solutions that align with the requirements of embedded systems.

The dissertation project will be based on a real-world scenario and will develop your ability to analyse situations, identify key issues, select, synthesise, and apply techniques and skills from different modules and to be able to evaluate the appropriateness of your solutions when compared to industrial practice.

Modules are subject to change and availability.

Assessment

We'll assess you in several ways including time-constrained assessments, coursework assignments, presentations and a major project. Our dissertation project and module case studies assess your ability to analyse situations, identify key issues, select, synthesise and apply techniques and skills from different modules, and evaluate the appropriateness of solutions when compared to industrial practice.

The dissertation artefact will be based on a real-world scenario.

Core Modules

• Embedded Systems Essentials with Arm
• IoT and Machine Learning at the Edge on Arm
• Machine Learning Techniques
• Prompt Engineering and Generative AI
• Postgraduate Major Project

Entry Requirements

Applicants will normally hold a first or second class first degree. While a prior degree in a subject containing computing or electronics is welcome, the course is open to applicants with an electronics / computing background and a passion for technology whose first degrees may be in other subjects.

A Foundation degree in computing or electronics with an appropriate period of industrial experience may also be considered. Each applicant for the Master’s programme who possesses a Foundation degree will be expected to attend an interview where an assessment will be made to determine the standard of their industrial experience and suitability for the course.

If English is not your first language, you will be expected to demonstrate a certificated level of proficiency of at least IELTS 6.5 or equivalent English Language qualification as recognised by ARU. You’ll need at least 5.5 in each of the four skills - listening, speaking, reading and writing.

As a distance learner, you'll also need a suitable computer with internet connection, together with sufficient IT competence to make effective use of our online Learning Management System (LMS) with high-speed internet and email. You will also need access to a fairly modern laptop or personal computer which runs Microsoft Windows 10 or later. Furthermore, admin rights are required to install relevant software packages.

Fees and Paying for University

Tuition Fees for Distance Learning Students (2024/25)

£8,200 Distance learning students starting 2024/25 (total cost)

ARU graduates may be eligible for an Alumni Scholarship and get a 20% fee discount.

Fees are payable upfront, in full or in instalments, but there's no need to pay until you've accepted an offer to study with us. Find out more about paying your fees and about postgraduate loans and funding.

Additional Costs

You will be required to purchase some hardware, such as ST DISCO-L475E, and sensors, which we do not expect to exceed £100.

Important Fee Notes

The part-time course fee assumes that you're studying at half the rate of a full-time student (50% intensity). Course fees will be different if you study over a longer period. All fees are for guidance purposes only.

Facilities

Join our postgraduate student community and:

• learn from expert staff who will guide your research interests and career development
• receive full support from our Employability Service, while you're studying with us and after you graduate
• access support, should you need it, with study skills, health and wellbeing, and more.

Careers

This course uniquely combines two popular topics – embedded computing and machine learning – meaning that you can feel confident you are investing your time building skills in specialisms that are sought-after within the industry. It’s ideal for those who wish to advance their existing careers in the technology sector, but also graduates who wish to pursue a Master’s degree.

The MSc in Embedded Computing and Machine Learning is strategically designed to immerse you in the dynamic realm of embedded systems, with a particular focus on acquiring industry relevant skills on Arm-based microcontrollers. The modules within our program not only provide theoretical knowledge but also offer practical exposure, ensuring that you're not just proficient in embedded computing concepts, but ready to contribute meaningfully to the industry.

Potential job roles that relate to this MSc could include Software Engineer, Embedded Systems Engineer, Hardware or Software Architect/Developer, Applications Developer or Data Architect/Engineer.

Graduation doesn't have to be the end of your time with us. You might decide to continue your academic career and join a research programme at ARU. Take advantage of our Alumni Scholarship and save £400 on your fees.