The educational objective of the present course is to bring the student closer to some applications of Artificial Intelligence (AI) and Machine Learning (ML) in the engineering and artistic fields. The course is therefore designed in two parts: the first concerns AI applications to electrical energy and information engineering; the second focuses on the use of ML techniques for musical and artistic production in general. Thus, the student will have the opportunity to learn how AI is a very versatile and performing tool in application fields that are very distant culturally.
teacher profile teaching materials
- Introductory notes on algorithms and problem solving from an engineering point of view
- Evolutionary Calculation: Genetic Algorithms, Swarm Intelligence.
- The Neural Networks.
- Programming languages and development environments: python.
2. Application of artificial intelligence in industrial and information engineering
- Application of Evolutionary Calculus for optimization and inverse problems in materials engineering, energy and biomedical fields.
- Neural, genetic and swarm intelligence models applied to the modeling of materials and devices.
- Application of AI and machine learning in design.
3. Applications of AI to music and art in general
- ML techniques for musical composition. How to computerize the musical signal: MIDI.
- Generative artificial intelligence in the visual and literary arts.
Programme
1. Algorithms and artificial intelligence- Introductory notes on algorithms and problem solving from an engineering point of view
- Evolutionary Calculation: Genetic Algorithms, Swarm Intelligence.
- The Neural Networks.
- Programming languages and development environments: python.
2. Application of artificial intelligence in industrial and information engineering
- Application of Evolutionary Calculus for optimization and inverse problems in materials engineering, energy and biomedical fields.
- Neural, genetic and swarm intelligence models applied to the modeling of materials and devices.
- Application of AI and machine learning in design.
3. Applications of AI to music and art in general
- ML techniques for musical composition. How to computerize the musical signal: MIDI.
- Generative artificial intelligence in the visual and literary arts.
Core Documentation
Zhng, A., Lipton, Z. C., Li, M., & Smola, A. J. (2021). Dive into deep learning. arXiv preprint arXiv:2106.11342. Available online: https://d2l.ai/Reference Bibliography
Zhng, A., Lipton, Z. C., Li, M., & Smola, A. J. (2021). Dive into deep learning. arXiv preprint arXiv:2106.11342. Disponibile online: https://d2l.ai/ Intelligenza Artificiale e arte - ISBN-13 978-8816606012 Editore Jaca Book Data di pubblicazione 5 novembre 2020Type of delivery of the course
Face-to-face Course: traditional classroom delivery methodType of evaluation
Discussion of course topics with open questions.