About

The project directly tackles the critical issue of digital transformation by significantly enhancing the effectiveness and quality of educational activities in Artificial Intelligence. It simultaneously elevates the digital readiness of participating higher education institutions, along with their current and future students. Moreover, it addresses one of the European Union’s major contemporary challenges: preparing a skilled workforce capable of supporting smart specialization strategies and excelling internationally. The project (no. 2023-1-PL01-KA220-HED-000166765) will last 36 months (until 30 September 2026). The total budget of the project is EUR 400,000.00.

Objectives

The main objective of the project is to improve the quality of higher education through the development and pilot implementation in an international consortium of 5 universities of AI/ML modules, and research projects. The achievement of this goal will be supported by numerous dissemination and activities, as well as by the cooperation of 5 universities and one associated partner.

The project aims to:

• Enhance students' knowledge and practical skills using newly developed educational materials.
• Increasing innovation and internationalization of the institutions involved through the exchange of good practices.
• Develop and promote an enriched study program and teaching materials with the promotion of open education.
• Increasing the didactic competencies of academic teachers.

Expected Results

The result of the project is the development of 64 ECTS (702 teaching hours) within 14 didactic modules in the fields of AI and ML. A strong emphasis will be placed on developing student potential and talents in the field of AI and ML - the project assumes the implementation of a pilot edition of students' scientific research projects that will focus on the use of AI and ML in environmental protection issues. Students will be equipped to research issues such as plastics and air pollution. The outcomes of all stages of the project’s pilot phase will be evaluated in a comprehensive study, leading to the development of a research-based teaching methodology. This will offer valuable resources to facilitate the effective use of the project’s results by interested recipients.

Structure

The University of Silesia is the leader of the project. The project is implemented in cooperation with the following partners:

• University of Zagreb (UNIZG), Croatia
• Pavol Jozef Šafárik University in Kosice (UPJS), Slovakia
• Vilnius University (VU), Lithuania
• University of Maribor (UM), Slovenia

By integrating the expertise of consortium teachers and modern teaching methods, the project will successfully implement diverse teaching units. These units will comprehensively cover broad aspects of data engineering for data science, fundamental and advanced Artificial Intelligence techniques, and their various applications to data analysis.

An associated partner of the project is Oracle Academy which will support the consortium teachers and students during the project. Cooperation with Oracle Academy will provide access to resources and contacts of this organization specializing in cooperation with Citizen Data Scientists and ML services.

Students Projects

The project includes a pilot edition of student scientific research projects focused on applying AI to environmental protection issues. Topics of Student Research Projects aim at Solving Disruptive Environmental Problems within the Idea of Teaching by Conducting Research:

Artificial Intelligence & Machine Learning Methods for Solving Air Pollution Problems & Adverse Climate Changes

• Improving Air Pollution Sensors using AI/ML methods (University of Silesia, Pavol Jozef Šafárik University in Kosice).
• Exploring the Climate Activity Datasets using AI/ML methods towards the best reduction in CO2 emissions (University of Silesia, Pavol Jozef Šafárik University in Kosice).
• AI/ML to Improve the Energy Efficiency of Buildings Aimed at Reducing the Negative Impact on the Environment (University of Maribor, University of Zagreb).

Artificial Intelligence & Machine Learning Methods for Solving Problems with Plastics in Environment

• Studying Effects of Plastics on Proteins & Biomembranes by using MD simulations and Searching for Solutions of Problems with Plastics in Environment using AI/ML Methods (University of Silesia, Pavol Jozef Šafárik University in Kosice).
• Predicting the Outcome of Solar Power Plants (Vilnius University).