- Docente: Simone Martini
- Credits: 2
- SSD: INF/01
- Language: Italian
- Moduli: Simone Martini (Modulo 1) Stefano Pio Zingaro (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
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Corso:
Percorso abilitante in
B016 - Percorso Abilitante 30 Cfu ai Sensi dell'Allegato 2 Del DPCM 4 Agosto 2023 - Laboratori di Scienze e Tecnologie Informatiche (cod. 6112)
Also valid for Percorso abilitante in A041 - Scienze e Tecnologie Informatiche (cod. 6081)
Percorso abilitante in B016 - Laboratori di Scienze e Tecnologie Informatiche (cod. 6085)
Percorso abilitante in A041 - Percorso Abilitante 30 Cfu ai Sensi dell'Allegato 2 Del DPCM 4 Agosto 2023 - Scienze e Tecnologie Informatiche (cod. 6106)
Learning outcomes
At the end of the course, the student has acquired critical knowledge of certain epistemological aspects of computer science. He knows, and is able to distinguish, the main scientific, technological and operational contributions of the discipline, setting them in their historical context.
Knows some formalisations of the informal concept of 'effective' and the limits of those formalisations (i.e. that there are problems that do not admit of effective solutions).
Knows how to discuss and frame certain social and ethical issues related to the discipline.
Will have acquired a thorough understanding of the historical evolution of Artificial Intelligence, from the deterministic to the probabilistic approach, analysing its impact on the discipline and society. The various aspects of AI, such as reasoning, planning and learning will be explored, with a focus on the foundations of machine learning and the recent deep learning revolution.
Course contents
Epistemological aspects: computer science as a set of digital tools, as technology, as science.
Some of the founding ideas and essential knowledge of computer science (concepts of interpreter, algorithm, program, protocol, info representation, ...), in the educational perspective.
International reference models:
K-12 CS Framework (2016) and CSTA K-12 Computer Science Standards
Limitations of effective procedures
Teaching programming in the age of generative computing
Some social and ethical aspects (pe. The 'Vienna manifesto for digital humanism')
Historical aspects: evolution of Artificial Intelligence from deterministic to probabilistic approach.
Founding ideas: reasoning, planning and learning.
Tools: use of educational platforms such as Machine Learning for Kids, Teachable Machine and other interactive tools for teaching machine learning and deep learning.
International reference models: exploration of international standards and guidelines for teaching Artificial Intelligence in schools.
Social and ethical impacts: analysis of the effects of Artificial Intelligence on society, including ethical and moral aspects, interpretability, accountability, trustworthiness, explainability and related techniques.
Readings/Bibliography
Articles, slides, material to be made available during the course, on virtuale.unibo.it
Teaching methods
Lectures with discussion
Assessment methods
Provided that the minimum mandatory percentage of participation is confirmed and that possible assignments have been handed in as requested during the lectures, the assessment of the learning outcome of the course will take place during the final examination for the teaching qualification in the focal discipline, as stated in the Art. 9 of the DPCM 08/04/2023.
Office hours
See the website of Simone Martini
See the website of Stefano Pio Zingaro