Studiare all’Unipi: corsi, iscrizioni e servizi per ogni fase del percorso accademico, dall’orientamento alle opportunità postlaurea
Servizi e opportunità per accompagnare chi studia a Pisa nel percorso universitario, in un campus integrato nella città
Con la nostra ricerca, espandiamo la frontiera della conoscenza e prepariamo persone pronte a contribuire al futuro della società
Valorizziamo la conoscenza in un rapporto aperto con le imprese e la società per la crescita culturale, sociale ed economica del Paese
Promuoviamo la diffusione del sapere e sosteniamo le trasformazioni sociali, partecipando al progresso della comunità e del territorio
L’identità di Unipi: la sua storia, i valori che la guidano e la visione del futuro, tra tradizione, innovazione e impegno per la comunità
Language: English
Period: 2 – 13 February 2026
Application Deadline: 2 January 2026
Program Intensity: Full-time
ECTS: 6
Tuition fees: 500€
Archaeology deals with the study of the human past, conducted through material remains, i.e. artefacts that were manufactured, used, and discarded in ancient times. One of the most important tasks is to classify the artefacts, determining chronology, cultural attribution, form, function and other features. Neural networks and deep learning are powerful tools for supporting and facilitating such tasks, often time-consuming and heavily depending on prior knowledge and expertise.
The “AI for Archaeologists, with Python” Winter School illustrates the use of neural networks for analysing and classifying multimodal data, such as images, tables, and texts. It is conducted, with a hands-on approach, through Python, one of the main programming languages of AI and Data Science, including a wide variety of deep learning tools and network architectures. In order to effectively conduct and support the analysis and classification of data coming from tables, images and texts, modern archaeologists should be able to deal with concepts and tools related to new technologies. Such skills are not present in a standard archaeology background, though they are fundamental even to effectively interact with ICT experts.
Bibliography: Stevens E., Antoga L., Viehmann T., Deep Learning with Pytorch, Manning (2020).
The Winter School will be activated with at least 10 students. The maximum number of participants is set to 40 students.
The Winter School will last 60 hours, from 2 to 13 February 2026, and it will take place on campus in Pisa, at the Department of Civilisations and Forms of Knowledge, in Via Trieste, 40.
The program will be activated also in distance learning mode (TEAMS platform).
The Winter School will enable participants to explore and visualize data with Python, set up and train neural networks from scratch and/or by modifying pre-trained networks (transfer learning), in order to perform classification tasks based on images and/or texts. It is built around a new paradigm, which takes into consideration archaeologists as both producers and users of digital archaeological data. A key component of the Winter School will focus on using effective prompting strategies encouragind a critical and informed use of Large Language Models, such as ChatGPT, Gemini or Copilot.
Students, graduates, PhD candidates, and post-docs in archaeology or related to Cultural Heritage.
Admission Requirements
Specific computer science or technology skills are not required.
For an effective learning environment, the number of participants will be limited to 40 students.
Personal laptops are needed for attending the summer school. Some introductory tutorials will be delivered to attendees before the School starts.
Required documents:
All the documents must be in pdf format, in order to upload them on the portal when required.
Application has to be submitted via Alice portal following the instructions of the “How to apply” page.
Tuition fees: 500€
Pay fees by Debit/Credit Card or PayPal online using the following Payment Form.
Important notice: the payment form will be available from 7 January 2026.
Notice:
Refund policy
Tuition fees are not refundable. The Winter School will be activated (and consequently, payments will be requested) only upon reaching the minimum number of participants necessary for activation.
Coordinator
Prof. Gabriele Gattiglia gabriele.gattiglia@unipi.it
Dr. Nevio Dubbini nevio.dubbini@unipi.it
Website http://www.mappalab.eu/
Summer/Winter School Office support.summerschool@unipi.it