Course Syllabus
Obiettivi
Conoscenza e comprensione
Lo studente acquisirà conoscenze avanzate sull’intelligenza artificiale, l’apprendimento automatico, le tecnologie di comunicazione e la loro integrazione nelle applicazioni intelligenti in ambito consumer. Verranno compresi concetti fondamentali come l’elaborazione di segnali, immagini, voce e linguaggio naturale, la personalizzazione e la tutela della privacy nei sistemi connessi.
Capacità di applicare conoscenza e comprensione
Lo studente sarà in grado di progettare, implementare e valutare sistemi intelligenti per il consumatore utilizzando framework e strumenti moderni di deep learning. Le conoscenze teoriche saranno applicate a scenari pratici come le smart home, l’healthcare e l’Internet of Things.
Autonomia di giudizio
Lo studente svilupperà la capacità di analizzare criticamente le scelte tecnologiche nei sistemi intelligenti, valutare approcci di progettazione user-centered e riflettere sulle implicazioni etiche e relative alla privacy.
Abilità comunicative
Lo studente sarà in grado di presentare e discutere in modo efficace le soluzioni tecnologiche, le scelte progettuali e i risultati dei progetti, sia in forma scritta che orale, utilizzando un linguaggio tecnico preciso e adeguato in contesti multidisciplinari.
Capacità di apprendimento
Il corso favorisce lo sviluppo dell’autonomia nello studio e nell’approfondimento delle tecnologie intelligenti per il consumatore, stimolando l’aggiornamento continuo sulle tendenze emergenti e la capacità di trasferire le competenze acquisite in nuovi ambiti.
Contenuti sintetici
Il corso è composto da una parte teorica e da una parte pratica.
La parte teorica mira a esplorare l'intelligenza artificiale, l'apprendimento automatico, le tecnologie di comunicazione e le tecnologie di consumo. La parte pratica mira ad approfondire l'ecosistema ICT dal punto di vista applicativo attraverso l'analisi di applicazioni di rilevamento intelligente in ambito domestico, nella sanità, ecc.
La parte pratica consiste in esercizi di base e avanzati che utilizzano framework di deep learning.
Programma esteso
Moduli del corso:
- Course Presentation: An overview of the course structure, objectives, and key learning outcomes.
- Introduction to Intelligent Consumer Technologies: A broad introduction to the field, exploring its history, current trends, and future potential.
- Signal Processing in Consumer Devices:
- Speech Processing: Understanding how devices process spoken commands and interact vocally with users.
- Image Processing: Techniques for enhancing, recognizing, and interpreting images by digital devices.
- Inertial Processing: Exploration of how devices use inertial sensors to provide context-aware functionalities.
- Personalization Technologies: Examining how devices use data to customize and adapt their functionalities to individual user preferences.
- Communication Technologies: Insight into the technologies that enable devices to connect and communicate, including WiFi, Bluetooth, and NFC.
- Privacy in Intelligent Consumer Technologies: Critical analysis of privacy issues, focusing on data security, user rights, and ethical design principles.
Obiettivi Formativi:
Upon completion of this course, students will:
- Understand the fundamental concepts of signal processing as applied to voice, image, and motion.
- Gain insight into how consumer technologies are personalized and how they communicate.
- Be able to identify and discuss the technological underpinnings of intelligent consumer devices.
Prerequisiti
Fondamenti di AI, Machine e Deep Learning, Fondamenti di tecnologie di comunicazione, Fondamenti di programmazione
Modalità didattica
L’insegnamento prevede una parte di lezioni teoriche che si terranno in aula, e una parte di laboratorio che si terranno in laboratorio e/o in aula e che richiederanno l’uso del proprio PC. Entrambe le parti saranno basate sia su didattica erogativa che interattiva.
Materiale didattico
• Scientific articles suggested by the teacher.
• Teachers' slides (http://elearning.unimib.it/)
• GitHub of the course:
1. https://github.com/paolonapoletano
2. https://github.com/CeLuigi
Periodo di erogazione dell'insegnamento
Primo Semestre
Modalità di verifica del profitto e valutazione
L'esame consiste nell'ideazione e nella realizzazione di un progetto assegnato dal docente (o autoproposto) sulle tecnologie di consumo intelligenti. Il progetto può essere sviluppato individualmente o in collaborazione con un collega. Il progetto sarà discusso sotto forma di presentazione orale e i docenti potranno porre domande sulle parti teoriche e pratiche del corso.
Orario di ricevimento
Paolo Napoletano, Lunedi from 14 to 16
Luigi Celona, Lunedi from 14 to 16
Ionel Eduard Stan, Lunedi from 14 to 16
Sustainable Development Goals
Aims
Knowledge and understanding
Students will acquire advanced knowledge of artificial intelligence, machine learning, communication technologies, and their integration in intelligent consumer applications. They will understand key concepts such as signal, image, speech and natural language processing, personalization, and privacy in connected systems.
Applying knowledge and understanding
Students will develop the ability to design, implement, and evaluate intelligent consumer systems using modern deep learning frameworks and tools. They will apply theoretical knowledge to practical scenarios such as smart home, healthcare, and IoT applications.
Making judgements
Students will be able to critically analyze the technological choices in intelligent systems, assess user-centered design approaches, and reflect on ethical and privacy-related implications.
Communication skills
Students will learn to effectively present and discuss technological solutions, design decisions, and project outcomes, both orally and in writing, using clear and technically accurate language in interdisciplinary contexts.
Learning skills
The course fosters the ability to autonomously deepen knowledge in the field of AI-powered consumer technologies, stay updated on emerging trends, and transfer acquired skills to new domains.
Contents
The course consists of a theoretical part and a practical part.
The theoretical part aims at exploring artificial intelligence, machine learning, communication technologies and consumer technologies. The practical part aims to deepen ICT ecosystem from an applied perspective by analyzing intelligent sensing applications in home environment, in healthcare etc.
The practical part consists in basic and advanced exercises using deep learning frameworks.
Detailed program
Course Modules:
- Course Presentation: An overview of the course structure, objectives, and key learning outcomes.
- Introduction to Intelligent Consumer Technologies**: A broad introduction to the field, exploring its history, current trends, and future potential.
- Signal Processing in Consumer Devices:
- Speech Processing: Understanding how devices process spoken commands and interact vocally with users.
- Image Processing: Techniques for enhancing, recognizing, and interpreting images by digital devices.
- Inertial Processing: Exploration of how devices use inertial sensors to provide context-aware functionalities.
- Personalization Technologies: Examining how devices use data to customize and adapt their functionalities to individual user preferences.
- Communication Technologies: Insight into the technologies that enable devices to connect and communicate, including WiFi, Bluetooth, and NFC.
- Privacy in Intelligent Consumer Technologies: Critical analysis of privacy issues, focusing on data security, user rights, and ethical design principles.
Learning Outcomes:
Upon completion of this course, students will:
- Understand the fundamental concepts of signal processing as applied to voice, image, and motion.
- Gain insight into how consumer technologies are personalized and how they communicate.
- Be able to identify and discuss the technological underpinnings of intelligent consumer devices.
Prerequisites
Fundamental of AI, Machine and Deep Learning, Fundamental of Communication Technologies, Fundamental of programming.
Teaching form
The teaching includes a part of theoretical lectures that will be held in the classroom, and a part of laboratory that will be held in the laboratory and/or classroom and will require the use of one's own PC. The two parts will be based both on delivery mode and interactive mode.
Textbook and teaching resource
• Scientific articles suggested by the teacher.
• Teachers' slides (http://elearning.unimib.it/)
• GitHub of the course:
1. https://github.com/paolonapoletano
2. https://github.com/CeLuigi
Semester
First semester
Assessment method
The exam consists in the design and realization of a project assigned by the teacher (or self-proposed) about intelligent consumer technologies. The project can be developed individually or in collaboration with one colleague. The project will be discussed as an oral presentation and the teachers can ask questions about the theoretical and practical parts of the course.
Office hours
Paolo Napoletano, Monday from 14 to 16
Luigi Celona, Monday from 14 to 16
Ionel Eduard Stan, Monday from 14 to 16
Sustainable Development Goals
Key information
Staff
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Luigi Celona
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Paolo Napoletano
-
Ionel Eduard Stan