MSc Artificial Intelligence (with placement)

In this course, you'll learn how to deploy, manage, and maintain AI technologies within the business value chain. You will gain the skills to work as part of an interdisciplinary team that include AI expert practitioners, who will be tasked with designing and developing systems that meet business requirements.When you graduate, you will understand AI principles, concepts, techniques and methods to support the integration of fully developed AI technologies into existing information technology systems by adapting the existing systems to interface with the new technologies.The course puts theory into practice through skills development relevant to the modern world, particularly the industrial application of artificial intelligence. It offers skills development as an integral part of the curriculum and as preparation for the world of work. As well as practical skills necessary for the Computing professional, with emphasis on design and development, students will develop transferable skills which will make them suitable for graduate employment in an ever-changing job market.This course is available to students with some prior knowledge of quantitative research methods and experience in software engineering practice, for example, graduates of the Q-step Social Sciences with Quantitative Methods undergraduate degree courses who may also have software development experience through previous work.The year-long paid work placement is an important feature of the course. It is optional, but if chosen, it will give you a distinct advantage in graduating. We have an excellent placements office to support finding a right placement opportunity for each student. One year paid work placement option available.

You will need:Applicants should have a UK honours degree (2.2 minimum) or equivalent in a technical or scientific subject* (excluding students with an initial degree in AI or data sciences disciplines);Applicants with relevant employment experience or other relevant qualifications will also be considered*including, but is not limited to, sport science, biomedical sciences, environmental science, mathematics, statistics, economics, accounting, information systems, computer science, cybersecurity, software engineering and other engineering disciplines such as civil, mechanical, electronic, chemical, etc.