Master in Archival science and AI

At Università degli Studi della Tuscia, tuition fees are 1,275 EUR per year.

Archival Science and AI is a master's degree taught in English at Università degli Studi della Tuscia in Viterbo, Italy, over two years. This program combines archival science, which concerns the organization, preservation, and management of documents and records, with the application of artificial intelligence tools to archival work. Students typically study the principles of archival theory and practice, records management, and digital preservation, alongside subjects covering how computational and artificial intelligence methods can be applied to the description, search, and analysis of archival collections. Coursework often addresses the transition from paper-based to digital archives, the standards used to catalogue and preserve records, and the emerging role of automated tools in processing large volumes of archival material, giving students both a traditional grounding in archival practice and an introduction to the technologies reshaping the field. Because archives increasingly exist in digital form and contain volumes of material too large to process manually, the discipline trains students to combine archival expertise with computational approaches to organizing and making information accessible. Graduates commonly pursue careers as archivists and records managers within public archives, libraries, museums, and cultural institutions, as well as within organizations that manage large digital document collections. Others move into roles focused on digital preservation, information management, or the application of artificial intelligence tools within cultural heritage and information science settings. The degree can also serve as a foundation for further research in archival science, digital humanities, or information science. Based in Viterbo and delivered entirely in English, the program is designed for students interested in the intersection of archival tradition and emerging digital and AI-based methods.