MSc Artificial Intelligence with a Human Face

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 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.

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.

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.