Course summary
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.
Modules
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
Assessment method
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.
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.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Provider information
Anglia Ruskin University
East Road
Cambridge
CB1 1PT