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
- Why AI: classification, clustering and prediction
- Methods of searching for the optimum.
- Programming languages and development environments: python, matlab, C
2. Application of artificial intelligence in industrial and information engineering
- Application of Evolutionary Calculation for the optimization of the performance of renewable energy sources
- Applications of Neural Networks for the prediction of energy needs (seasonality).
- 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.
- Generative artificial intelligence in the visual arts
- Development of applications for graphics engines
Fruizione: 20810085 METODI DI SIMULAZIONE PER CIRCUITI E SISTEMI ELETTRICI ED ELETTRONICI in Ingegneria elettronica per l'industria e l'innovazione LM-29 RIGANTI FULGINEI FRANCESCO
Programme
1. Algorithms and artificial intelligence- Introductory notes on algorithms and problem solving from an engineering point of view
- Why AI: classification, clustering and prediction
- Methods of searching for the optimum.
- Programming languages and development environments: python, matlab, C
2. Application of artificial intelligence in industrial and information engineering
- Application of Evolutionary Calculation for the optimization of the performance of renewable energy sources
- Applications of Neural Networks for the prediction of energy needs (seasonality).
- 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.
- Generative artificial intelligence in the visual arts
- Development of applications for graphics engines
Core Documentation
Zhang, A., Lipton, Z. C., Li, M., & Smola, A. J. (2021). Dive into deep learning. arXiv preprint arXiv:2106.11342. Available online: https://d2l.ai/Type of delivery of the course
Oral examinationAttendance
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