Course summary

Artificial intelligence technologies are being increasingly adopted across a broad range of industries, creating demand for talented graduates who can help realise the transformative potential of AI. With a fundamental interest in AI, machine vision and computer sciences, you will have the desire to apply this knowledge to solve real world engineering problems. Taught through a unique combination of theoretical and practical-based sessions you will cover subjects in logic and reasoning, data analytics, deep learning, agent architectures, alongside the broader systems engineering and ethical considerations required for implementation in real-world systems. Who is it for? This course provides engineering, physics, computing or mathematics graduates with the advanced skills which can be applied to the security, defence, marine, environmental and aerospace industries. This course is also available on a part-time basis enabling you to combine studying with full-time employment. Why this course? Artificial intelligence (AI) and machine learning are redefining the way we live and work, allowing us to automate processes and enhance productivity. These new technologies create the need for skilled engineers with an understanding of their applications and intricacies. Increasingly, governments are outlining AI and data revolutions as areas of priority to ensure global leadership for the industries of the future. By embedding AI, government agendas aspire to create new, high-quality jobs and drive economic growth. Undertaking this course will allow you to be at the forefront of this ongoing technological revolution, equipping you with both the theoretical and practical knowledge to work across disciplines and implement AI systems where they are needed. We are well located for visiting part-time students from all over the world, and offer a range of library and support facilities to support your studies, while balancing work/life commitments. Our MSc programmes benefit from a broad cultural diversity of students, which significantly enhances the learning experience for both staff and students. Informed by industry The course is directed by an Industrial Advisory Panel who meet twice a year to ensure that it provides the right mix of hands-on skills and up-to-date knowledge suitable to the wide variety of applications that this field addresses. The panel will also propose industry relevant research challenges that will shape the topics for individual thesis projects. A number of members also attend the annual student thesis presentations which take place a month or so before the end of the course. This provides a good opportunity for students to meet key employers.