The MSc Responsible Artificial Intelligence is a well-integrated programme of study with a targeted focus on both in theory and in application. Presupposing no background in computing, students are equipped with relevant knowledge and data programming skills, covering not only recent technical developments, but also broader ethical and theoretical considerations.
MSc Responsible Artificial Intelligence
MSc Responsible Artificial Intelligence
Full-time or part-time
One year (FT) or two years (PT)
19th September 2022 (see term dates)
|Annual tuition fees:||
Home: £11,000 (FT) /£5,500 (PT)
International: £14,000 (FT) / £7,000 (PT)
|Faculty & Research:|
The option to study philosophical issues of AI whilst pursuing a Masters level computing degree is a unique offering in the UK, allowing students the opportunity to delve on the technical as well as the societal impact of data processing and, in particular, machine learning applications. Read more
The programme allows students to progressively develop their understanding of the techniques of data science, machine learning, and natural language processing, alongside key concepts and methods of computer science, while honing their programming skills in Python and Java; and, at the same time, refine their thinking and communication skills, through humanities courses devoted to a consideration of key practical and theoretical issues, arising in connection with AI.
The MSc Responsible Artificial Intelligence consists of eight taught courses, six courses (90 credits) in Computer and Data Science and two courses (30 credits) in the Humanities, plus an individual software development project (60 credits). Read more
The six computing courses teach students the theory and application of computer and data science, especially in relation to Artificial Intelligence (AI). They are taught in pairs, one per term. In each pair, one course always complements the teaching of its counterpart. In Michaelmas term, students learn the basics of programming (e.g. control flow statements and data collections), alongside the fundamentals of computing (e.g. logic operators, algorithm complexity and data structures). In Hilary, students learn how to ingest and transform data (e.g. numerical arrays, images or text), alongside how to design and structure programs. Finally, in Trinity students learn how to develop machine learning applications at breadth and depth. We choose Natural Language Processing to study depth because it has a profound technical and societal impact nowadays and it is pertinent to humanics.
The two humanities courses teach students to think carefully and communicate clearly about philosophical (ethical and other) issues arising in relation to computing, data usage, AI, and other emerging technologies.
The individual project offers an opportunity to students to pursue impactful interdisciplinary projects on an agreed topic of their choice in digital humanities or computational social sciences within the college and with its partners. It runs throughout the year so that students have ample time to focus their independent learning with the right guidance by their supervisor(s). Students will gain experience interacting with non-technical audiences to gather problem specifications and explain solutions.
Teaching & learning
The MSc Responsible Artificial Intelligence will be delivered through a mixture of lectures, seminars, lab-based tutorials and office hours. Read more
Students who are enrolled full-time should anticipate devoting approximately 35-40 hours per week to their studies for the duration of their degree. In Michaelmas and Hilary terms, this will include approximately six to seven formal contact hours per week, with the remainder consisting of structured independent study.
The Masters programme can be taken part-time over two years. Part-time students attend the same classes as their full-time colleagues, taking 50% of the course load each academic year. The classes are not run separately in the evening for part-time students. Read more
While we try to make the part-time study as flexible as possible, our Master’s programmes are demanding and we advise students that, if they intend to work alongside the course, their work should be flexible.
Timetables are usually made available to students during Freshers’ Week. Teaching can be scheduled to take place during any day of the week. However, when possible, Wednesday afternoons are usually reserved for sports and cultural activities.
Artificial Intelligence and, more specifically, the application of machine learning techniques to big data sets is becoming increasingly prevalent in society. There is an increasing need in the tech and public sector for graduates who can not only develop machine learning applications well, but who can also understand the issues that arise in relation to such applications; and who can communicate technical and societal issues clearly.