Computing Science/History of Art

Computing science and history of art make an unexpectedly rich pairing, connecting one of the most technically demanding of the applied sciences with one of the most critically and historically sophisticated of the humanities. Computing science provides the logical, mathematical, and engineering foundations for understanding and building computational systems, from algorithms and data structures to artificial intelligence and human-computer interaction. History of art examines the visual arts across cultures and historical periods, asking how images and objects are made, what meanings they carry, how they relate to their social and intellectual contexts, and how they have been interpreted over time.

At the University of Glasgow, this four-year full-time degree allows you to pursue both subjects to an advanced level. In computing science you will develop strong foundations in programming, algorithms, software engineering, computer systems, and artificial intelligence, building the technical depth and problem-solving capability that the discipline requires. In history of art you will engage with art across multiple periods and cultural traditions, developing visual analysis, critical writing, and art historical method.

The programme includes a year abroad, which enriches both the academic and personal dimensions of your degree significantly.

The combination is particularly relevant in an era when the intersection of digital technology and the visual arts is generating new questions about image analysis, digital humanities, cultural heritage preservation, and the use of computational methods in art historical research. You will be one of very few graduates equipped to engage seriously with both sides of that conversation.

Graduates from computing science and history of art programmes move into careers in digital humanities research, museums and cultural heritage, software development, technology roles in the creative industries, art and auction house research, and academia. The dual expertise is increasingly sought as cultural institutions invest in digital transformation and as computational methods become more central to art historical scholarship.