Neural Networks for Archaeologists, with Python ~ UNIPI

Language: English

Period: 3 – 14 February 2025

Application deadline: 29 December 2024

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 “Neural Networks 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 these technologies. Such skills are not present in a standard archaeology background, though they are fundamental to effectively nteracting with ICT experts.

Bibliography: Stevens E., Antoga L., Viehmann T., Deep Learning with Pytorch, Manning (2020).

The Winter School will last 60 hours, from February 3rd to 14th, 2025, 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).

Aim

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.

Who can apply

Students, graduates, PhD candidates, and post-docs in archaeology or related to Cultural Heritage.

Application

Admission Requirements

Specific computer science or technology skills are not required.
For an effective learning environment, the number of participants will be limited to 20 students.
Personal laptops are needed for attending the summer school. Some introductory tutorials will be delivered to attendees before the School starts.

Important notice:

The Winter School will be activated with at least 10 students.
The maximum number of participants is set to 20 students.
The application deadline was originally set to 20 December 2024. The one above indicated is the new application deadline due to the postponement from 20 December 2024 to 29 December 2024 (at 11:59 pm CET).

Required documents:

Identity Document (PASSPORT in case you are a foreign student)
Enrolment Form
Curriculum Vitae

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.

Fees

Tuition fees: 500€

Pay fees by Debit/Credit Card or PayPal online using the following:Payment Form.

Notice:

International students without Italian Tax Code: please tick the box ‘Anonymous’ in order to disable the field ‘Italian personal ID/VAT number’.
Please type your NAME and SURNAME next to the pre-filled text of the field ‘Reason’.
Please pay only after receiving the admission letter.

Refund policy

Tuition fees will be refunded only in case of cancellation of the Winter School.

Fundings

Please write to the coordinator to get information.

Contacts

Coordinator

Prof. Gabriele Gattiglia gabriele.gattiglia@unipi.it

Dr. Nevio Dubbini nevio.dubbini@gmail.com

Website http://www.mappalab.eu/

Summer/Winter School Office support.summerschool@unipi.it

Didattica

Campus e Servizi

Ricerca

Innovazione

Università e Società

Ateneo

News

Neural Networks for Archaeologists, with Python

Contacts