Master in Artificial Intelligence for Archaeology and Cultural Heritage
A 1-year programme to become an AI specialist for Archaeology and Cultural Heritage.
2-nd level Master โข 60 ECTS
ย Learn how to apply Artificial Intelligence, Machine Learning, computer vision, GIS, and digital technologies to archaeological research and cultural heritage management through an interdisciplinary programme combining computer science and archaeology.
Why study AI for Archaeology?
Artificial intelligence is reshaping how archaeological data are collected, analysed and interpreted. From satellite imagery and predictive modelling to computer vision for artefact classification and large language models for historical texts, AI enables researchers to tackle questions that were previously impossible at scale.
Graduates are increasingly needed in universities, museums, cultural heritage institutions, public agencies and technology companies working with digital heritage.
What you will learn
During the programme you will learn to:
- Develop AI and machine learning models for archaeological applications
- Analyse spatial data using GIS and geospatial AI
- Process archaeological images with computer vision
- Use Large Language Models for textual analysis
- Build semantic databases and knowledge graphs
- Create digital twins and 3D reconstructions
- Develop reproducible research workflows in Python
- Apply robotics and remote sensing technologies in archaeology
View the call for applications and apply via the University of Pisa website
9 Modules
The program supports professional placement in both public and private sectors, characterized by high levels of technological
innovation.
Career opportunities include the design of information systems and digital platforms, the development of tools for
automated data analysis, and employment in universities, heritage institutions, cultural organizations, research centers, and
companies in the digital heritage sector, as well as advanced research roles.
The Masterโs program responds to the growing demand for professionals capable of integrating archaeological expertise with
artificial intelligence in the context of the digital transformation of cultural heritage. It prepares graduates to manage and analyze
complex and heterogeneous data (including images, 3D models, and spatial and textual data), develop computational models for
interpretation, and design innovative solutions for research, conservation, and public access to heritage.
1.Digital Archaeology and AI for Cultural Heritage
The module explores how AI supports the documentation, analysis, interpretation, and dissemination of archaeological data, integrating images, spatial information, and textual sources into digital research workflows.
2. Python Programming for Archaeology
Introduction to Python programming for archaeological research, focusing on data analysis, archaeological datasets, and the automation of digital research workflows through reproducible scripts and practical applications.
3. Databases, Ontologies, and the Semantic Web
Relational and graph databases for cultural heritage, focusing on semantic data modeling, CIDOC CRM, SPARQL, and linked open data to support interoperability, integration, and knowledge discovery.
4. Statistical Methods for Archaeology
The module covers statistical methods for archaeological data analysis, covering descriptive and inferential statistics, regression, clustering, and multivariate analysis to support quantitative interpretation and data-driven research.
5. Intro to Robotics for Archaeological Documentation and Monitoring
Introduction to ground and aerial robotics for archaeology, focusing on drones and robotic systems for site documentation, monitoring, mapping, 3D reconstruction, and data collection in complex environments.
6. Intro to AI and Machine Learning for Archaeology, with Python
Artificial intelligence and machine learning, covering supervised and unsupervised learning, neural networks, and model development in Python, using archaeological datasets.
7. 3D Modeling and Information Systems for Cultural Heritage
3D documentation and heritage information systems, covering digital photogrammetry, 3D reconstruction, HBIM, and semantic approaches to the documentation and analysis of archaeological contexts.
8. GIS, Spatial Analysis, and Artificial Intelligence
Advanced spatial analysis for archaeology, integrating Geographic Information Systems (GIS) and artificial intelligence for spatial modeling, predictive analysis, geospatial machine learning, and data visualization.
9. Artificial Intelligence for Image and Text Processing, Large Language Models
Artificial intelligence for visual and textual data analysis in archaeology, covering computer vision, natural language processing, and large language models for image analysis, information extraction, and research support.
Hands-on Learning
Learning is centred on practical experience. Throughout the programme, students work with real archaeological datasets and digital heritage case studies, through laboratory sessions and project-based activities. The programme concludes with an individual project tackling a real research or cultural heritage challenge.
Technologies you’ll work with
- ๐ Python
- ๐ค Machine Learning
- ๐ GIS
- ๐๏ธ Computer Vision
- ๐ฌ LLMs
- ๐๏ธ Databases
- ๐ง 3D Modelling
- ๐ SPARQL
- ๐ธ๏ธ CIDOC CRM
- ๐ง Neural Networks
- ๐ Open Dataย
Why University of Pisa and MAPPA Lab?
Study at one of Europe’s leading centres for digital archaeology and artificial intelligence applied to cultural heritage. At MAPPA Lab, you’ll learn from researchers developing innovative methods in AI, GIS, computer vision, robotics, 3D technologies, and heritage data management, while working with real archaeological datasets and case studies in a research-driven environment.
The Masterโs programme is part of the PA 110 e lode initiative, offering an important opportunity for italian public administration employees.
- ๐ International research collaborations
- ๐ช๐บ Participation in European research projects
- ๐ฌ Research-led teaching
- ๐บ Access to real archaeological datasets and case studies
- ๐ค Interdisciplinary expertise in archaeology and AI
Career opportunities
The rapid adoption of artificial intelligence and digital technologies is creating new opportunities across archaeology, cultural heritage, and the wider digital humanities sector. Graduates of the programme will be equipped with the interdisciplinary skills needed to bridge the gap between archaeological research and advanced computational methods.
Career opportunities include positions in:
- ๐๏ธ Museums and cultural heritage institutions
- ๐บ๏ธ Archaeological and heritage consultancy
- ๐ Public heritage agencies and international organisations
- ๐ค AI and geospatial technology companies
- ๐ Data analysis and digital innovation
- ๐ Universities and research centres
- ๐ฌ PhD programmes in archaeology, artificial intelligence, digital humanities, and related disciplines
Graduates will be prepared to contribute to the development of innovative solutions for archaeological research, heritage documentation, digital preservation, and the sustainable management of cultural heritage.
Admissions: who should apply
The Masterโs is designed for graduates who wish to combine archaeological knowledge with artificial intelligence and digital technologies. It welcomes applicants from diverse academic backgrounds who are interested in developing innovative solutions for the study, management, and preservation of cultural heritage.ย The programme is also particularly relevant to:
- graduates seeking to develop practical skills in artificial intelligence, machine learning, and emerging technologies for applications in archaeology and cultural heritage;
- researchers seeking to integrate artificial intelligence, data science, and digital methods into archaeological or cultural heritage research;
- professionals working in archaeology, museums, cultural heritage institutions, consultancy, technology, or related sectors who wish to expand their digital and computational expertise;
- public-sector officials and cultural heritage officers who are involved in the documentation, protection, management, enhancement, or communication of cultural heritage.
Applicants may come from academic backgrounds including:
- Archaeology and Cultural Heritage
- Computer Science and Artificial Intelligence
- Engineering
- Geography and Geomatics
- Architecture
- Digital Humanities and Information Science
- Other related disciplines with an interest in artificial intelligence and cultural heritage
Admission remains subject to the formal degree requirements specified in the official call for applications.
No advanced programming experience is required. Participants will progressively develop practical skills in Python, machine learning, GIS, computer vision, and other digital technologies throughout the programme.
FAQ
Is the programme taught in English?
Yes. All lectures, course materials, and assessments are delivered in English.
Who can apply?
The programme is open to graduates from eligible disciplines such as archaeology, cultural heritage, computer science, engineering, geography, architecture, digital humanities, and related fields. Please refer to the admission requirements for full eligibility criteria.
Do I need programming experience?
No. Previous programming experience is not required. The programme includes introductory courses in Python and progressively develops practical skills in AI and digital technologies.
What software and technologies will I learn?
Students gain hands-on experience with Python, machine learning, GIS, computer vision, large language models, databases, semantic technologies, photogrammetry, 3D modelling, and other tools widely used in digital archaeology and cultural heritage.
Is the programme practical?
Yes. Practical activities are integrated throughout the programme. Students work with real archaeological datasets, laboratory exercises, and project-based assignments, culminating in an individual research project..
What career opportunities does the programme offer?
Graduates are prepared for careers in museums, cultural heritage institutions, archaeological consultancies, research centres, public agencies, and technology companies, as well as for doctoral studies.