Machine learning and deep neural networks are at the heart of today’s technological revolution, driving innovation across nearly every sector – from healthcare and finance to robotics, transportation and the creative industries. This MSc is designed to equip you with the applied, industry-relevant expertise and practical skills needed to capitalise in the dynamic and fast-growing intelligent and smart systems domains.
Delivered jointly by the Departments of Electronic & Electrical Engineering (EEE) and Computer & Information Sciences the course offers a truly interdisciplinary learning experience. You’ll benefit from the combined strengths of both departments—gaining insights from leading academics in autonomous and intelligent control, machine learning, deep neural networks, data analytics and software engineering.
Through a blend of theoretical study and hands-on learning, you’ll develop a deep understanding of how intelligent systems are designed, built, and deployed. You’ll also engage with real-world challenges and industry case studies, learning to use the programming languages and engineering tools that drive innovation in today’s products and services.
Whether you're aiming to join a leading technology company, contribute to cutting-edge research, or launch your own AI-driven venture, this course provides the technical foundation, design proficiency expertise and career-ready skills to help you succeed.
"The combination of specialist engineering and computer science classes offered in this MSc ensures graduates possess the technical and practical skills needed to create tomorrow’s innovative and impactful AI systems."
Dr Gaetano Di Caterina Course Director
You’ll study a selection of taught modules exploring all major aspects of machine learning, intelligent systems and deep neural networks, with a focus on robotics, data science and decision-making technologies. These modules are designed to develop advanced knowledge in these topics, enhanced with the leadership, project management and professional engineering skills sought after by employers.
Check key dates for your MSc and the University academic session.
Students who pass all required taught modules will progress to the MSc Project, undertaken between May and August, and culminating with the Poster Presentation Day, where they will have the opportunity to showcase their research. MSc Projects involve an in-depth investigation on a topic chosen by the student within the field of electronic or electrical engineering. Projects may be:
While all projects are designed to address real-world engineering challenges, competitive internships offer additional benefits, including:
This course structure ensures that students graduate with not only academic knowledge but also practical experience and industry insight.
In the video below, MSc students talk about their studies and projects at the department's Poster Presentation Day:
This MSc aims to equip students with the industry-relevant skills and expertise to help shape the AI systems of the future. You’ll:
Academic requirements Normally a first-class or second-class honours degree (or international equivalent) in electronic or electrical engineering, or computer science. Highly-qualified candidates from other relevant engineering or science-related disciplines may be considered. Don’t meet the academic entry requirements? We offer the Pre-Masters Preparation Course at the University of Strathclyde International Study Centre, for international students (non-UK/Ireland). English language requirements If English is not your first language, please visit our English language requirements page for full details of the requirements in place before making your application.