The Department of Automated Control Systems, the Institute of Computer Science and Information Technologies, Lviv Polytechnic, invites bachelors’ and masters’ students to participate in the Winter School «A European Approach to Data Governance», which will take place online on February 2–6, 2026.
The purpose of the event is to:
- familiarize participants with the European Data Strategy and data management in accordance with EU legislation;
- introduce the prospects for creating a single European data market and examine the legal aspects of the lawful collection, storage, and analysis of personal data;
- provide an overview of the fundamentals of data science, including data analysis and visualization, machine and deep learning, cloud services and technologies, as well as the basics of data security;
- examine the specifics of working with sensitive data, with particular attention to the impact of the GDPR on the processing of medical data.
To participate in the Winter School, it is necessary to register by January 31, 2026.
Participant selection will be conducted on a competitive basis. Applicants will be notified of the selection results by February 1.
Students will have the opportunity to receive 1.5 ECTS credits, which may be transferred to relevant courses. To obtain a certificate, students must attend at least 80% of classes and submit an individual written assignment by February 15, 2026. The minimum passing score for the assignment is 40%.
The Winter School «A European Approach to Data Governance» is held by Lviv Polytechnic National University within the framework of the educational project of the Jean Monnet Module «European Data Strategy: Data Governance for New Opportunities» (№ 101127839 – Data4EU – ERASMUS-JMO-2023-HEI-TCH-RSCH) of the Erasmus+ program with the support of the European Union. The classes will be conducted by project participants.
The Winter School will also include master classes, workshops, and practical sessions led by invited speakers from leading Ukrainian IT companies, focusing on the principles of Big Data, machine learning, data analytics and visualization, and data security.
