Degree Course: Computer science and engineering
A.Y. 2024/2025
Conoscenza e capacità di comprensione
Il laureato magistrale in Ingegneria Informatica avrà (i) conoscenze e capacità di comprensione che, estendendo e rafforzando quelle acquisite nella formazione di primo livello, consentono di elaborare e applicare idee originali, (ii) competenze avanzate ad ampio spettro nell'area dell'ingegneria informatica e in alcune sue specifiche sotto-aree, (iii) visione interdisciplinare dei problemi e degli strumenti metodologico/applicativi.
Questi obiettivi sono perseguiti attraverso gli insegnamenti erogati in entrambi gli anni di corso, soprattutto quelli di natura formale e metodologica, e sono verificati attraverso gli esami di profitto.
Capacità di applicare conoscenza e comprensione
Il laureato magistrale sarà in grado di applicare le conoscenze acquisite alla risoluzione di problemi complessi relativi anche a tematiche nuove o non familiari, inserite in contesti più ampi (anche interdisciplinari) connessi all'ingegneria informatica.
In tale ambito, il laureato sarà in grado di integrare conoscenze e di condurre, sia autonomamente che in gruppi di lavoro, attività di analisi, progettazione, realizzazione, valutazione e gestione di sistemi di grandi complessità, nonché di formulare giudizi sulla base di informazioni limitate o incomplete.
Questi obiettivi sono perseguiti attraverso gli insegnamenti erogati in entrambi gli anni, soprattutto attraverso quelli più sperimentali e che danno spazio ad attività che prevedono lo sviluppo di progetti, anche da svolgere in gruppo.
Sono inoltre perseguiti attraverso le attività relative alla tesi di laurea magistrale.
La verifica avviene attraverso gli esami di profitto e l'esame di laurea magistrale.
Autonomia di giudizio
Il laureato magistrale in Ingegneria informatica sarà in grado di assumere responsabilità decisionali autonome in merito all'analisi, alla progettazione e alla valutazione di soluzioni informatiche, nel loro contesto applicativo, nell'ambito di progetti e sistemi complessi e di grandi dimensioni, nonché di partecipare attivamente a processi decisionali in contesti anche interdisciplinari.
Questa autonomia di giudizio viene perseguita soprattutto attraverso gli insegnamenti che prevedono una componente progettuale e la predisposizione di relazioni su tali attività progettuali, nonché attraverso le attività legate alla tesi di laurea magistrale e alla predisposizione di un relativo elaborato scritto.
Questo obiettivo viene verificato attraverso i relativi esami di profitto e la prova finale.
Abilità comunicative
Il laureato magistrale sarà in grado di comunicare e interagire efficacemente sulle tematiche di interesse con interlocutori specialisti e non specialisti, anche di alto livello, sia per comprendere e analizzare le loro necessità e i loro interessi specifici, che per prendere e valutare decisioni progettuali, nonché per comunicare e spiegare le proprie decisioni progettuali e le loro conseguenze.
Queste abilità comunicative vengono perseguite attraverso gli esami e attraverso la tesi di laurea magistrale.
In particolare, sono importanti le attività che prevedono una componente progettuale, da svolgere individualmente oppure in gruppo, nonché la stesura di relazioni per documentare tali attività progettuali.
È inoltre previsto un corso dedicato alla comunicazione con il mondo del lavoro e alle soft skill.
Questo obiettivo viene verificato attraverso la predisposizione di forme diversificate per gli esami di profitto (prove scritte, prove orali e relazioni di attività progettuali) e soprattutto attraverso la prova finale (che prevede sia la scrittura dell'elaborato di tesi magistrale che una sua esposizione orale), consentendo di valutare in modo complessivo le capacità di sintesi, comunicazione ed esposizione raggiunte.
Capacità di apprendimento
Il laureato magistrale sarà in grado di procedere in maniera autonoma nell'aggiornamento professionale, per rinnovare le proprie conoscenze ed acquisire nuove conoscenze anche in relazione alle continue evoluzioni delle tecnologie e metodologie informatiche.
Queste capacità di apprendimento vengono perseguite in particolare attraverso alcuni insegnamenti che prevedono una componente seminariale, di ricerca bibliografica e di classificazione della letteratura tecnico/scientifica.
Le capacità vengono ulteriormente consolidate attraverso la tesi di laurea magistrale.
Questo obiettivo viene verificato attraverso i relativi esami di profitto e la prova finale.
Requisiti di ammissione
Per poter accedere al Corso di Laurea magistrale in Ingegneria Informatica lo studente deve essere in possesso di una laurea nella classe L-8 Ingegneria Informatica oppure nella classe L-31 Scienze e tecnologie Informatiche.
Alternativamente, se laureato in classi diverse dalla L-8 ed L-31, lo studente deve aver conseguito almeno 24 CFU nei settori scientifico-disciplinari dell'area MAT e almeno 36 CFU complessivi nei settori scientifico-disciplinari ING-INF/05 o INF/01
Inoltre sono ammessi i possessori di altro titolo acquisito all'estero e riconosciuto idoneo.
Si rinvia al regolamento didattico del corso per la disciplina delle modalità di verifica delle personale preparazione.
La verifica della personale preparazione è obbligatoria in ogni caso, e possono accedervi solo gli studenti in possesso dei requisiti curriculari; in particolare, tale possesso non può essere considerato come verifica della personale preparazione.
In base all'analisi del curriculum individuale dello studente sarà eventualmente possibile individuare percorsi, sotto forma di piani di studio individuali all'interno della laurea magistrale, che conducano al conseguimento della laurea con 120 CFU, senza attività formative aggiuntive.
L'accesso alla Laurea Magistrale in Ingegneria Informatica prevede, inoltre, una verifica dell'adeguatezza della preparazione personale degli studenti, le cui modalità sono definite nel regolamento didattico.
Infine, il possesso di competenze nella lingua inglese che consenta ai laureati di utilizzare fluentemente, in forma scritta e orale, almeno una lingua dell'Unione Europea oltre l'italiano, con riferimento anche ai lessici disciplinari, come richiesto dalla classe di laurea, viene verificato richiedendo in accesso un livello equivalente al B2 del QCER secondo le modalità indicate nel regolamento didattico del corso.
Prova finale
La prova finale è costituita dalla discussione di una tesi di laurea magistrale originale, elaborata in modo autonomo dal candidato.
In particolare, la tesi deve essere relativa ad una significativa attività nell'ambito dell'Ingegneria Informatica, svolta dal candidato presso l'Università oppure presso un'azienda o un ente, sotto la guida di un relatore ed eventualmente di uno o più co-relatori, in cui è normalmente richiesta l'applicazione delle conoscenze e delle capacità apprese nei corsi di insegnamento, spesso con l'integrazione di conoscenze aggiuntive e la formulazione di proposte innovative.
Orientamento in ingresso
Le azioni di orientamento in ingresso sono improntate alla realizzazione di processi di raccordo con la scuola secondaria di secondo grado.
Si concretizzano sia in attività informative e di approfondimento dei caratteri formativi dei Corsi di Studio (CdS) dell'Ateneo, sia in un impegno condiviso da scuola e università per favorire lo sviluppo di una maggiore consapevolezza da parte degli studenti e delle studentesse nel compiere scelte coerenti con le proprie conoscenze, competenze, attitudini e interessi.
Le attività promosse si articolano in:
a) incontri e iniziative rivolte alle future matricole;
b) incontri per la presentazione delle Lauree Magistrali rivolte a studenti delle triennali;
c) sviluppo di servizi online (pagine social, sito), realizzazione e pubblicazione di materiali informativi sull'offerta formativa dei CdS (guide di dipartimento, guida breve di Ateneo, newsletter dell'orientamento).
L'attività di orientamento prevede una serie attività, distribuite nel corso dell'anno accademico, alle quali partecipano tutti i Dipartimenti e i CdS:
• Orientamento Next Generation Roma Tre, il progetto comune di tutti gli Atenei della Regione Lazio, a cui partecipa attivamente anche Roma Tre, è stato avviato nell'a.a.
2022- 2023 e si concluderà nel 2026.
Finanziato dai fondi del PNRR, è pensato per sostenere le studentesse e gli studenti della nostra Regione nella scelta consapevole del proprio percorso di formazione successivo al ciclo scolastico, nonché a definire la propria traiettoria personale e professionale.
Nel primo anno di attivazione Roma Tre ha raggiunto:
- 2.597 studenti inseriti in piattaforma del terzo o quarto anno di corso del target iniziale;
- presenze effettive: 2.330 studenti, che hanno raggiunto il 70% delle presenze;
- N.
125 corsi erogati;
- N.
accordi con le scuole: 14 convenzioni firmate
- N° Formatori interni: più di 100
• Giornate di Vita Universitaria (GVU), si svolgono ogni anno nell'arco di circa 3 mesi e sono rivolte a studentesse e studenti degli ultimi due anni della scuola secondaria superiore.
Si svolgono in tutti i Dipartimenti dell'Ateneo e costituiscono un'importante occasione per le future matricole per vivere la realtà universitaria.
Gli incontri sono strutturati in modo tale che accanto alla presentazione dei Corsi di Laurea, studentesse e studenti possano anche fare un'esperienza diretta di vita universitaria con la partecipazione ad attività didattiche, laboratori, lezioni o seminari, alle quali partecipano anche studenti seniores che svolgono una significativa mediazione di tipo tutoriale.
Partecipano annualmente circa 4.000 studenti; nel 2023 hanno partecipato 3.255 studenti in presenza.
Inoltre le GVU 2023 hanno totalizzato su YouTube 4.266 visualizzazioni.
• Incontri nelle scuole: nel 2023 l'Ufficio orientamento ha ricevuto 36 inviti.
Le richieste sono state lavorate nel seguente modo:
- se la scuola ha richiesto la presentazione dell'offerta formativa dell'intero Ateneo sono stati organizzati gli incontri di “Orientamento tra pari”: l'idea nasce dalla consolidata esperienza legata all'importanza di realizzare un orientamento, basato sul peer tutoring.
Nel 2023 sono stati realizzati 5 incontri on line alla presenza del personale dell'Ufficio con i borsisti (sia dei dipartimenti che dell'ufficio) presso:
a) il Liceo Peano di Roma (52 studenti);
b) Liceo artistico Caravaggio di Roma (200 studenti);
c) Liceo Metelli di Terni (20 studenti);
d) IT Fermi di Sulmona (200 studenti);
e) Informagiovani Roma Capitale (60 studenti)
Per un totale di 530 studenti.
Presso l'Assistant College Counseling St Stephen's School di Roma l'Ufficio è stato presente solo con un banchetto per la distribuzione di guide in inglese e in italiano a circa 60 studenti.
Si evidenzia che partecipano varie scuole di altre Regioni, grazie alla possibilità dell'online.
- se la scuola richiede un incontro specifico con uno o più dipartimenti, concordemente con quanto stabilito in Gloa (Gruppo di Lavoro per l'Orientamento di Ateneo) ogni invito viene inoltrato ai referenti Gloa presso i dipartimenti e le scuole, affinché realizzino i loro incontri;
• Attività di orientamento sviluppate dai singoli Dipartimenti, mediante incontri in presenza e online;
• Orientarsi a Roma Tre nel 2023 si è svolta in presenza presso il Nuovo Palazzo degli Uffici di Via Ostiense 133.
Nelle aule del dipartimento di Giurisprudenza sono state organizzate le presentazioni dell'offerta formativa dei Dipartimenti che sono state seguite anche in diretta streaming e che poi sono state caricate su YouTube.
I servizi sono stati presentati nelle torri, dove sono state distribuite le guide e dove le segreterie didattiche hanno anche organizzato delle postazioni con attività laboratoriali.
La sera è stato offerto un concerto di musica dal vivo ai partecipanti.
Hanno partecipato all'evento circa 4.000 studenti.
• Salone dello Studente a ottobre – novembre di ogni anno l'Ufficio orientamento partecipa all'evento organizzato da Campus presso la Nuova Fiera di Roma.
Il 17-19 ottobre 2023 è stato affittato uno stand lineare lungo 8 mt e organizzato con dei monitor dove giravano i PPT elaborati dall'Ufficio.
Sono stati distribuiti 8000 zaini e 8000 guide di Ateneo e bigliettini QR code.
Sono stati incontrati nelle aule più di 1.500 studenti in presenza e on line.
• Open Day Magistrali tra aprile e maggio 2023 è stata organizzata la prima edizione del progetto che ha visto lo sviluppo di 13 eventi dipartimentali utili a presentare l'Offerta magistrale e il post lauream.
Hanno partecipato 857 studenti, soprattutto di Roma Tre.
I servizi di orientamento online messi a disposizione dei futuri studenti universitari sono nel tempo aumentati, tenendo conto dello sviluppo delle nuove opportunità di comunicazione tramite web e tramite social.
Inoltre, durante tutte le manifestazioni di presentazione dell'offerta formativa, sono illustrati quei siti web di Dipartimento, di Ateneo, Portale dello studente, etc., che possono aiutare gli studenti nella loro scelta.
Infine, l'Ateneo valuta, di volta in volta, l'opportunità di partecipare ad ulteriori occasioni di orientamento in presenza ovvero online (Euroma2 e altre iniziative).
Il Corso di Studio in breve
Il Corso di Laurea Magistrale in Ingegneria Informatica dell'Università degli Studi Roma Tre offre un ampissimo e moderno ventaglio di insegnamenti di alto livello di specializzazione.
Tali insegnamenti coprono tutte le aree dell'Ingegneria Informatica e varie discipline affini.
Gli studenti possono caratterizzare la propria formazione scegliendo tra quattro curricula che rispecchiano i trend più innovativi dell'Ingegneria Informatica.
Il curriculum Sistemi Informatici Complessi ha vincoli ridotti e consente a ciascuno studente la definizione del piano di studi personalizzato più vicino ai propri interessi culturali e professionali.
Gli altri tre curricula sono concepiti per approfondire tre tematiche chiave dell'Ingegneria Informatica moderna.
Il curriculum Ingegneria dei Dati focalizza l'attenzione sul ruolo fondamentale dei dati in tutti i sistemi informatici.
Il curriculum Intelligenza Artificiale e Machine Learning approfondisce una delle metodologie/tecnologie più attuali del settore.
Il curriculum Algoritmi, Big Data e Machine Learning mostra come tre tecnologie chiave possano interagire dando luogo a sistemi scalabili innovativi.
Ognuna di queste scelte forma professionisti del settore informatico con un'elevata qualificazione, in grado di operare efficacemente in numerosi settori applicativi, capaci di risolvere problemi complessi e in grado di adeguarsi ai rapidi mutamenti tipici dei settori hi-tech.
L'efficacia di ciascuno di questi curricula all'avanguardia è testimoniato dal successo professionale dei nostri laureati sia in Italia che all'estero.
Le aziende più qualificate del settore contribuiscono alle attività didattiche anche attraverso progetti congiunti, convegni, workshop e seminari.
Varie startup di successo in campo informatico sono state fondate da Laureati Magistrali in Ingegneria Informatica di Roma Tre.
Opportunità formative all'estero sono inoltre incoraggiate e sostenute, sia attraverso i programmi Erasmus sia mediante progetti di tesi presso le università, enti di ricerca esteri e aziende estere che collaborano con la nostra Università.
Gli insegnamenti prevedono esercitazioni pratiche svolte in laboratori all'avanguardia, nei quali la didattica si fonde continuamente con l'innovazione e con la ricerca, anche grazie a un corpo docente di alta qualificazione scientifica.
Parte degli insegnamenti sono svolti in lingua inglese da docenti internazionali di elevata qualificazione, selezionati ogni anno su temi di attualità.
Le attività didattiche si svolgono in un campus organizzato e piacevole, vicino al centro di Roma, e raggiungibile facilmente con mezzi pubblici.
Le aule sono accoglienti e sono situate nello stesso edificio che ospita gli studi dei docenti, facilitando così l'interazione tra studenti e docenti.
I laboratori didattici sono ampi, moderni e bene organizzati.
Gli studenti hanno inoltre a disposizione una nuova biblioteca ed ampi spazi per lo studio.
La mensa universitaria è vicina, così come gli impianti sportivi.
Il corso di studio è ad accesso libero, senza alcuna prova in ingresso, e il requisito richiesto è il possesso di una laurea nella Classe delle Lauree in Ingegneria dell'Informazione o nella Classe delle Lauree in Scienze e Tecnologie Informatiche.
Inoltre, è necessario che lo studente abbia competenze di: analisi matematica, geometria ed algebra, fisica, ricerca operativa, fondamenti di informatica, algoritmi e strutture di dati, calcolatori elettronici, basi di dati, economia applicata all'Ingegneria, reti di calcolatori e programmazione orientata agli oggetti tipiche dei corsi di laurea in Ingegneria Informatica.
I Laureati in Università diverse da Roma Tre per accedere al corso di studio devono presentare una domanda di preiscrizione, documentando tutte le attività formative del proprio piano di studio relativo alla Laurea.
Il corso di studio è progettato per fornire tutte le competenze e conoscenze necessarie per consentire l'accesso ed una proficua fruizione di eventuali successivi corsi di dottorato di ricerca o master di secondo livello.
Esso appartiene alla classe delle lauree magistrali LM-32 in Ingegneria Informatica e consente l'accesso, previo superamento dell'Esame di Stato, all'Albo professionale dell'Ordine degli Ingegneri nella Sezione A, Settore dell'informazione.
Lo studente espliciterà le proprie scelte al momento della presentazione,
tramite il sistema informativo di ateneo, del piano di completamento o del piano di studio individuale,
secondo quanto stabilito dal regolamento didattico del corso di studio.
Sistemi Informatici Complessi
FIRST YEAR
First semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20810256 -
Automata, Languages and Computing
(objectives)
Introduce the students to the theory of languages and, at the same time, to the theory of automata. introduce computability and complexity paradigms. At the end of the course students should know new formal methodologies, should be able to critically review, from the perspective of their expressive potential, already known methodologies and should be able to classify problems from the point of view of the resources required for their solution.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
Optional Group:
curriculum Sistemi Informatici Complessi I ANNO quattro a scelta tra cinque insegnamenti - (show)
|
36
|
|
|
|
|
|
|
|
|
20801730 -
ARTIFICIAL INTELLIGENCE
(objectives)
The course aims to introduce advanced technologies of artificial intelligence, such as agent and multi-agent systems, probability-based reasoning, and the fundamentals of logic-based reasoning and decision support systems.
Developments in recent artificial intelligence models and technologies and their applications in the domains of major interest, such as robotics, AI-powered assistants, AI in education, finance, health-care and gaming, will be discussed.
The main and recent ethical, social and epistemological issues associated with the use of large-scale artificial intelligence tools and generative Artificial general intelligence will be discussed.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810007 -
ARCHITETTURA DEI SISTEMI SOFTWARE
(objectives)
The goal of the course is to present the discipline of software architecture, which is interested in studying the relationships between the structures of software systems and their quality attributes; this knowledge is fundamental for the analysis, design, evaluation and evolution of complex software systems. The course also presents the architecture of distributed software systems, the service-based architecture, and the software architecture for the Cloud, as well as some middleware services.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810259 -
Internet and Data Centers
(objectives)
The purpose is to provide advanced knowledge on computer networks and data centers, with methodological and technical contents. Special attention is devoted to scalability issues. At the end of the course the student is supposed to get the following concepts: inter-domain and intra-domain routing, congestion control, architectures for scalable systems. The student is also supposed to get advanced technicalities on widely adopted protocols. Finally, the student is supposed to understand the main economic and technical drivers of the internet and data centers evolution.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810260 -
Tecnologie e Architetture per la Gestione dei Dati
|
Also available in another semester or year
|
|
20810266 -
Machine Learning
|
Also available in another semester or year
|
|
|
Optional Group:
curriculum Sistemi Informatici Complessi - curriculum ingegneria dei Dati- curriculum Algoritmi, Big Data e Machine Learning-I ANNO due insegnamenti a scelta tra cinque - (show)
|
12
|
|
|
|
|
|
|
|
|
20810252 -
MODELS AND ALGORITHMS FOR OPTIMIZATION
(objectives)
The course aims at providing basic methodological and operative knowledge to represent and cope with decision processes and quantitative models.
|
6
|
MAT/09
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810208 -
Decision Support Systems and Analytics
(objectives)
The aim of the course is to present the main theoretical and methodological tools for modeling decisions and for identifying the best decision support strategies. The course also aims at providing the skills on how to use the available data in analytical prescriptive models, how to read the results provided by the adopted models and how to interpret them to propose appropriate solutions to complex management problems.
|
6
|
MAT/09
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810257 -
Diritto dei Dati
|
Also available in another semester or year
|
|
20801648 -
PROBABILITY AND STATISTICS
|
Also available in another semester or year
|
|
20810326 -
WIRELINE AND WIRELESS NETWORKS
(objectives)
The course describes the main characteristics and performance of wireline and wireless communication systems and networks: the physical layer features, data link protocols, switching techniques, medium access and data protection are described. The main architectures, technologies and protocols are described, that are used in fiber optic transport and access networks, 4G and 5G mobile networks, wireless local area networks (WLANs) and Internet of Things (IoT) networks.
|
6
|
ING-INF/03
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
|
Optional Group:
Curriculum Sistemi Informatici complessi: 12 cfu a scelta libera dello studente - (show)
|
12
|
|
|
|
|
|
|
|
|
20810323 -
QUANTUM COMPUTING
(objectives)
Present the computational paradigm of Quantum Computing. At the end of the course students should be able to understand even complex Quantum algorithms and to analyze and write simpler Quantum algorithms.
|
3
|
ING-INF/05
|
27
|
-
|
-
|
-
|
Elective activities
|
ITA |
|
Second semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
Optional Group:
curriculum Sistemi Informatici Complessi I ANNO quattro a scelta tra cinque insegnamenti - (show)
|
36
|
|
|
|
|
|
|
|
|
20801730 -
ARTIFICIAL INTELLIGENCE
|
Also available in another semester or year
|
|
20810007 -
ARCHITETTURA DEI SISTEMI SOFTWARE
|
Also available in another semester or year
|
|
20810259 -
Internet and Data Centers
|
Also available in another semester or year
|
|
20810260 -
Tecnologie e Architetture per la Gestione dei Dati
(objectives)
The goal of the course is to present models, methods and systems that play a fundamental role in database technology, together with discussions on the recent evolution of the technology itself. The directions of development to be considered include integration of heterogeneous and autonomous systems; databases for business intelligence and decision support. After taking the course, the student will know the major features of relational database technology, the methods for data integration, and for the design of data warehouses.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810266 -
Machine Learning
(objectives)
The course aims to provide advanced and specific competencies in recent machine learning models and technologies. The course will enable the solving of complex problems through appropriate problem formulation and definition of the most suitable models and knowledge representations, and the most efficient implementation techniques for machine learning algorithms. Reinforcement learning and state-of-the-art models, such as graph neural networks and tuning and self-tuning techniques, will be introduced.
The course consists of a theoretical and methodological part on advanced and innovative concepts, and a laboratory activity in which these concepts are applied in problem solving using the latest development frameworks.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
|
Optional Group:
curriculum Sistemi Informatici Complessi - curriculum ingegneria dei Dati- curriculum Algoritmi, Big Data e Machine Learning-I ANNO due insegnamenti a scelta tra cinque - (show)
|
12
|
|
|
|
|
|
|
|
|
20810252 -
MODELS AND ALGORITHMS FOR OPTIMIZATION
|
Also available in another semester or year
|
|
20810208 -
Decision Support Systems and Analytics
|
Also available in another semester or year
|
|
20810257 -
Diritto dei Dati
(objectives)
Provide an introduction to the main principles and rules concerning data governance under Italian and European law. Study the legal distinction between personal and non personal data, with reference to the main instruments related to property, access, and circulation of data (intellectual property, trade secret, personal data protection). Analyse the issues deriving from the use of data in algorithmic decisions, both in administrative and private law contexts.
|
6
|
IUS/02
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20801648 -
PROBABILITY AND STATISTICS
(objectives)
To provide the fundamental elements of probability theory and mathematical statistics, along with some tools of parametric statistics, which may be useful in practice.
|
6
|
MAT/06
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810326 -
WIRELINE AND WIRELESS NETWORKS
|
Also available in another semester or year
|
|
SECOND YEAR
First semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
Optional Group:
curriculum Sistemi Informatici Complessi II ANNO -quattro insegnamenti a scelta tra tredici - (show)
|
24
|
|
|
|
|
|
|
|
|
20801798 -
INTELLIGENT SYSTEMS FOR THE INTERNET
|
Also available in another semester or year
|
|
20802125 -
BIG DATA
|
Also available in another semester or year
|
|
20810006 -
ADVANCED TOPICS IN COMPUTER SCIENCE
|
Also available in another semester or year
|
|
20810140 -
CYBERSECURITY
(objectives)
The Cybersecurity course intends to provide the student with competencies needed for understanding and tackling cybersecurity problems for ICT systems and complex organizations, to design networks and computing systems with a certain level of security, and to planning e manage activities related to cybersecurity. The course provides competences about attacks, countermeasures, cryptographic tools, applications, and methodologies in the cybersecurity field. Advanced topics in data integrity are also addressed.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20802126 -
INFORMATION VISUALIZATION
|
Also available in another semester or year
|
|
20810205 -
Digital entrepreneurship
|
Also available in another semester or year
|
|
20810211 -
Algorithms for big data
(objectives)
In many application contexts huge volumes of data are produced which are
used in the economic-financial, political, social and even institutional
fields. Often the data is stored in huge distributed clouds and is
sometimes generated according to a continuous flow, so large as to make
complete storage unfeasible. In many cases the data pertains to entities
in close relationship with each other and gives rise to massive networks
of connections. Familiar examples for such networks are biological and
social networks, distribution networks, and the Web graph. Furthermore,
the fact that the data is stored in systems managed by third parties
poses integrity problems, which have not been considered in the
classical IT literature in terms of both their type and scale.
This scenario poses unprecedented algorithmic challenges, which are
being considered by a vast audience of researchers. In the last decade,
this effort has produced many innovations on both the methodological and
technological level. This course aims at transferring to the students
some of the most important methodological tools originated from the
research on Big Data algorithms. These methodological tools are
presented within challenging application contexts.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810223 -
INGEGNERIA DEI DATI
(objectives)
Providing skills on systems, methods, and technologies for extraction, cleaning, analyzing and integrating and management of unstructured data.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810261 -
Computer Graphics
(objectives)
This course aims at illustrating the modern software and hardware computer graphics architectures, and at providing mathematical, technical and methodological solutions for the development of projects concerning the visualization of data in 2D or 3D. The course will expose base concepts in computer graphics such as spaces, curves, surfaces and volumes, focusing on notions and algorithms currently used in scientific visualization, videogames, and computer animation. Moreover, this course aims at exposing details of hardware and software platforms currently in use.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20802136 -
CYBER PHYSICAL SYSTEMS
(objectives)
The design of Cyber-Physical Systems (CPS) requires multi-disciplinary skills. In particular, the combined knowledge of various disciplines such as, control theory, signal processing, fault detection, and real-time computing, is crucial for the effective developments of CPS. Consequently, the course aims at providing to the students basics on such thematic areas considering a system-oriented approach. Moreover, also innovative methodologies for fault diagnosis and protection of CPS will be discussed considering the direct study of advanced research papers.
|
6
|
ING-INF/04
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810262 -
Deep Learning
(objectives)
The course aims to provide advanced and specific skills in the area of the latest Deep neural network architectures. Particular attention will be given to multimodal models, and networks capable of analyzing complex data structures, such as graphs and multivariate time series; and deep reinforcement learning. At the end of the course, the student will be able to: adequately design and optimize Deep neural networks, be able to distinguish and evaluate different solutions, and be able to select and customize the most effective network architectures to be used in real application domains, supervised, unsupervised, or following a reinforcement learning approach. The course consists of a theoretical and methodological part on advanced and innovative concepts, and a laboratory activity in which these concepts are applied in problem solving using the latest development frameworks.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810263 -
Logica
(objectives)
The course aims at giving basic knowledge of classical and some non-classical logics, their formal semantics and proof systems. Students will acquire the capability to use the studied logics for representation purposes and will be presented with some important applications of logic in computer science.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810264 -
Pianificazione Automatica
|
Also available in another semester or year
|
|
|
20801785 -
SKILLS FOR THE WORLD OF WORK
|
Also available in another semester or year
|
Second semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20801785 -
SKILLS FOR THE WORLD OF WORK
(objectives)
Frequency seminars mandatory.
The course aims to present the main soft skills for employment access through seminars held by speakers from the production reality. The seminaris illustrate the job and career dynamics in different types of companies (startups, SMEs, multinationals) in different sectors (software integrators, service companies, product companies, insurance and banking groups, utilities). Soft skills include how to write an effective CV, how to address the job interview. The course also introduces basic notions of labor laws.
|
1
|
|
25
|
-
|
-
|
-
|
Other activities
|
ITA |
|
Optional Group:
curriculum Sistemi Informatici Complessi II ANNO -quattro insegnamenti a scelta tra tredici - (show)
|
24
|
|
|
|
|
|
|
|
|
20801798 -
INTELLIGENT SYSTEMS FOR THE INTERNET
(objectives)
The course will allow students to learn various methods for the design, implementation, and testing of adaptive systems on the Web, created through Artificial Intelligence techniques, with particular reference to Machine Learning techniques. Specific attention will be paid to Information Retrieval systems, such as search engines, crawlers and document feeds. Classic retrieval models will be studied, such as the Vector Space Model and probabilistic models, document ranking techniques, as well as the PageRank algorithm used by Google. Machine Learning methods in Information Retrieval will be addressed, including techniques for Sentiment Analysis, User Modeling methods necessary for personalized search, and social search applications involving communities of individuals in activities such as content tagging and question answering. The techniques for analyzing social networks (e.g., Facebook and Twitter) will be explored, which will allow us to explore phenomena such as the spread of fake news, the filter bubble, and the polarization of users. Finally, Recommender Systems will be studied, from basic algorithms (e.g., collaborative filtering) to application scenarios (e.g., movies, books, music artists and songs).
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20802125 -
BIG DATA
(objectives)
The goal of the course is to illustrate the modern solutions to the management of big data, very large repositories of de-structured data. Starting from the requirements of modern database applications, the course will illustrate the hardware and software architectures that have been recently proposed for the management and analysis of big data. The topics addressed in the course will include: cluster architectures, map-reduce paradigm, cloud computing, NoSQL systems, tools and languages for data analysis. Both theoretical and practical aspects will be addressed and the discussed technologies will be experimented during practical classes and through the assignment of projects.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810006 -
ADVANCED TOPICS IN COMPUTER SCIENCE
(objectives)
The goal of the course is to present models, methods and systems related to the latest advances in the field of information technology able to meet the requirements of modern applications. The course is taught in English by foreign professors of high qualification
|
6
|
ING-INF/05
|
42
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810140 -
CYBERSECURITY
|
Also available in another semester or year
|
|
20802126 -
INFORMATION VISUALIZATION
(objectives)
The goal of this course is that of introducing the participants to the problems and the solutions in the area of the visual exploration of abstract data, with a particular emphasis on the visual perception phenomena, on the graphic metaphors that can be exploited and on thealgorithmic methods and models that can be adopted. The
knowledge of the participants about algorithm engineering and network optimization problems will be deepened. Such a knowledge will be applied to different strains of visualization problems with a strong practical approach.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810205 -
Digital entrepreneurship
(objectives)
Provide students with technical and methodological skills
necessary to conceive, develop and implement a digital business project.
The course will be divided into three parts. The first part aims to explain the reasons behind the success of digital companies (especially, but not only, startups) and digital innovation dynamics. The second part offers students the technical and methodological tools for the realization of a digital business project. The third part consists in the realization of a project and is characterized by a strongly experimental approach.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810211 -
Algorithms for big data
|
Also available in another semester or year
|
|
20810223 -
INGEGNERIA DEI DATI
|
Also available in another semester or year
|
|
20810261 -
Computer Graphics
|
Also available in another semester or year
|
|
20802136 -
CYBER PHYSICAL SYSTEMS
|
Also available in another semester or year
|
|
20810262 -
Deep Learning
|
Also available in another semester or year
|
|
20810263 -
Logica
|
Also available in another semester or year
|
|
20810264 -
Pianificazione Automatica
(objectives)
The course presents Artificial Intelligence planning problems. It introduces models and resolution techniques for both "classic" and temporal planning, involving scheduling aspects. Different methodologies for the synthesis of action plans and their execution will be presented, as well as aspects related to automated learning of classical planning domains. Furthermore, some applications and samples will be presented and discussed, also in relation to the control of autonomous robots
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
|
20802019 -
FINAL EXAM
(objectives)
https://ingegneria.uniroma3.it/didattica/collegio-informatica/lauree-e-tirocini/laurea-magistrale/
|
26
|
|
650
|
-
|
-
|
-
|
Final examination and foreign language test
|
ITA |
Ingegneria dei Dati
FIRST YEAR
First semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20810256 -
Automata, Languages and Computing
(objectives)
Introduce the students to the theory of languages and, at the same time, to the theory of automata. introduce computability and complexity paradigms. At the end of the course students should know new formal methodologies, should be able to critically review, from the perspective of their expressive potential, already known methodologies and should be able to classify problems from the point of view of the resources required for their solution.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
Optional Group:
curriculum Sistemi Informatici Complessi - curriculum ingegneria dei Dati- curriculum Algoritmi, Big Data e Machine Learning-I ANNO due insegnamenti a scelta tra cinque - (show)
|
12
|
|
|
|
|
|
|
|
|
20810252 -
MODELS AND ALGORITHMS FOR OPTIMIZATION
(objectives)
The course aims at providing basic methodological and operative knowledge to represent and cope with decision processes and quantitative models.
|
6
|
MAT/09
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810208 -
Decision Support Systems and Analytics
(objectives)
The aim of the course is to present the main theoretical and methodological tools for modeling decisions and for identifying the best decision support strategies. The course also aims at providing the skills on how to use the available data in analytical prescriptive models, how to read the results provided by the adopted models and how to interpret them to propose appropriate solutions to complex management problems.
|
6
|
MAT/09
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810257 -
Diritto dei Dati
|
Also available in another semester or year
|
|
20801648 -
PROBABILITY AND STATISTICS
|
Also available in another semester or year
|
|
20810326 -
WIRELINE AND WIRELESS NETWORKS
(objectives)
The course describes the main characteristics and performance of wireline and wireless communication systems and networks: the physical layer features, data link protocols, switching techniques, medium access and data protection are described. The main architectures, technologies and protocols are described, that are used in fiber optic transport and access networks, 4G and 5G mobile networks, wireless local area networks (WLANs) and Internet of Things (IoT) networks.
|
6
|
ING-INF/03
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
|
Optional Group:
curriculum Ingegneria dei dati - I anno- tre insegnamenti a scelta tra di cui almeno due: Architetture dei sistemi software, Internet and Data Centers, Machine learning - (show)
|
27
|
|
|
|
|
|
|
|
|
20810007 -
Software Systems Architecture
(objectives)
The goal of the course is to present the discipline of software architecture, which is interested in studying the relationships between the structures of software systems and their quality attributes; this knowledge is fundamental for the analysis, design, evaluation and evolution of complex software systems. The course also presents the architecture of distributed software systems, the service-based architecture, and the software architecture for the Cloud, as well as some middleware services.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20801730 -
ARTIFICIAL INTELLIGENCE
(objectives)
The course aims to introduce advanced technologies of artificial intelligence, such as agent and multi-agent systems, probability-based reasoning, and the fundamentals of logic-based reasoning and decision support systems.
Developments in recent artificial intelligence models and technologies and their applications in the domains of major interest, such as robotics, AI-powered assistants, AI in education, finance, health-care and gaming, will be discussed.
The main and recent ethical, social and epistemological issues associated with the use of large-scale artificial intelligence tools and generative Artificial general intelligence will be discussed.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810259 -
Internet and Data Centers
(objectives)
The purpose is to provide advanced knowledge on computer networks and data centers, with methodological and technical contents. Special attention is devoted to scalability issues. At the end of the course the student is supposed to get the following concepts: inter-domain and intra-domain routing, congestion control, architectures for scalable systems. The student is also supposed to get advanced technicalities on widely adopted protocols. Finally, the student is supposed to understand the main economic and technical drivers of the internet and data centers evolution.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810266 -
Machine Learning
|
Also available in another semester or year
|
|
Second semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20810260 -
Tecnologie e Architetture per la Gestione dei Dati
(objectives)
The goal of the course is to present models, methods and systems that play a fundamental role in database technology, together with discussions on the recent evolution of the technology itself. The directions of development to be considered include integration of heterogeneous and autonomous systems; databases for business intelligence and decision support. After taking the course, the student will know the major features of relational database technology, the methods for data integration, and for the design of data warehouses.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
Optional Group:
curriculum Sistemi Informatici Complessi - curriculum ingegneria dei Dati- curriculum Algoritmi, Big Data e Machine Learning-I ANNO due insegnamenti a scelta tra cinque - (show)
|
12
|
|
|
|
|
|
|
|
|
20810252 -
MODELS AND ALGORITHMS FOR OPTIMIZATION
|
Also available in another semester or year
|
|
20810208 -
Decision Support Systems and Analytics
|
Also available in another semester or year
|
|
20810257 -
Diritto dei Dati
(objectives)
Provide an introduction to the main principles and rules concerning data governance under Italian and European law. Study the legal distinction between personal and non personal data, with reference to the main instruments related to property, access, and circulation of data (intellectual property, trade secret, personal data protection). Analyse the issues deriving from the use of data in algorithmic decisions, both in administrative and private law contexts.
|
6
|
IUS/02
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20801648 -
PROBABILITY AND STATISTICS
(objectives)
To provide the fundamental elements of probability theory and mathematical statistics, along with some tools of parametric statistics, which may be useful in practice.
|
6
|
MAT/06
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810326 -
WIRELINE AND WIRELESS NETWORKS
|
Also available in another semester or year
|
|
|
Optional Group:
curriculum Ingegneria dei dati - I anno- tre insegnamenti a scelta tra di cui almeno due: Architetture dei sistemi software, Internet and Data Centers, Machine learning - (show)
|
27
|
|
|
|
|
|
|
|
|
20810007 -
Software Systems Architecture
|
Also available in another semester or year
|
|
20801730 -
ARTIFICIAL INTELLIGENCE
|
Also available in another semester or year
|
|
20810259 -
Internet and Data Centers
|
Also available in another semester or year
|
|
20810266 -
Machine Learning
(objectives)
The course aims to provide advanced and specific competencies in recent machine learning models and technologies. The course will enable the solving of complex problems through appropriate problem formulation and definition of the most suitable models and knowledge representations, and the most efficient implementation techniques for machine learning algorithms. Reinforcement learning and state-of-the-art models, such as graph neural networks and tuning and self-tuning techniques, will be introduced.
The course consists of a theoretical and methodological part on advanced and innovative concepts, and a laboratory activity in which these concepts are applied in problem solving using the latest development frameworks.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
SECOND YEAR
First semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
Optional Group:
Curriculum Ingegneria dei dati - II anno due insegnamenti " a scelta tra" di cui almeno uno: Algoritmi per big data, Visualizzazione delle informazioni - (show)
|
12
|
|
|
|
|
|
|
|
|
20810006 -
ADVANCED TOPICS IN COMPUTER SCIENCE
|
Also available in another semester or year
|
|
20810211 -
Algorithms for big data
(objectives)
In many application contexts huge volumes of data are produced which are
used in the economic-financial, political, social and even institutional
fields. Often the data is stored in huge distributed clouds and is
sometimes generated according to a continuous flow, so large as to make
complete storage unfeasible. In many cases the data pertains to entities
in close relationship with each other and gives rise to massive networks
of connections. Familiar examples for such networks are biological and
social networks, distribution networks, and the Web graph. Furthermore,
the fact that the data is stored in systems managed by third parties
poses integrity problems, which have not been considered in the
classical IT literature in terms of both their type and scale.
This scenario poses unprecedented algorithmic challenges, which are
being considered by a vast audience of researchers. In the last decade,
this effort has produced many innovations on both the methodological and
technological level. This course aims at transferring to the students
some of the most important methodological tools originated from the
research on Big Data algorithms. These methodological tools are
presented within challenging application contexts.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810140 -
CYBERSECURITY
(objectives)
The Cybersecurity course intends to provide the student with competencies needed for understanding and tackling cybersecurity problems for ICT systems and complex organizations, to design networks and computing systems with a certain level of security, and to planning e manage activities related to cybersecurity. The course provides competences about attacks, countermeasures, cryptographic tools, applications, and methodologies in the cybersecurity field. Advanced topics in data integrity are also addressed.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810205 -
Digital entrepreneurship
|
Also available in another semester or year
|
|
20810263 -
Logica
(objectives)
The course aims at giving basic knowledge of classical and some non-classical logics, their formal semantics and proof systems. Students will acquire the capability to use the studied logics for representation purposes and will be presented with some important applications of logic in computer science.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20802126 -
INFORMATION VISUALIZATION
|
Also available in another semester or year
|
|
|
20801785 -
SKILLS FOR THE WORLD OF WORK
|
Also available in another semester or year
|
|
20810223 -
DATA ENGINEERING
(objectives)
Providing skills on systems, methods, and technologies for extraction, cleaning, analyzing and integrating and management of unstructured data.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
Second semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20801785 -
SKILLS FOR THE WORLD OF WORK
(objectives)
Frequency seminars mandatory.
The course aims to present the main soft skills for employment access through seminars held by speakers from the production reality. The seminaris illustrate the job and career dynamics in different types of companies (startups, SMEs, multinationals) in different sectors (software integrators, service companies, product companies, insurance and banking groups, utilities). Soft skills include how to write an effective CV, how to address the job interview. The course also introduces basic notions of labor laws.
|
1
|
|
25
|
-
|
-
|
-
|
Other activities
|
ITA |
|
20802019 -
FINAL EXAM
(objectives)
https://ingegneria.uniroma3.it/didattica/collegio-informatica/lauree-e-tirocini/laurea-magistrale/
|
26
|
|
650
|
-
|
-
|
-
|
Final examination and foreign language test
|
ITA |
|
Optional Group:
Curriculum Ingegneria dei dati - II anno due insegnamenti " a scelta tra" di cui almeno uno: Algoritmi per big data, Visualizzazione delle informazioni - (show)
|
12
|
|
|
|
|
|
|
|
|
20810006 -
ADVANCED TOPICS IN COMPUTER SCIENCE
(objectives)
The goal of the course is to present models, methods and systems related to the latest advances in the field of information technology able to meet the requirements of modern applications. The course is taught in English by foreign professors of high qualification
|
6
|
ING-INF/05
|
42
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810211 -
Algorithms for big data
|
Also available in another semester or year
|
|
20810140 -
CYBERSECURITY
|
Also available in another semester or year
|
|
20810205 -
Digital entrepreneurship
(objectives)
Provide students with technical and methodological skills
necessary to conceive, develop and implement a digital business project.
The course will be divided into three parts. The first part aims to explain the reasons behind the success of digital companies (especially, but not only, startups) and digital innovation dynamics. The second part offers students the technical and methodological tools for the realization of a digital business project. The third part consists in the realization of a project and is characterized by a strongly experimental approach.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810263 -
Logica
|
Also available in another semester or year
|
|
20802126 -
INFORMATION VISUALIZATION
(objectives)
The goal of this course is that of introducing the participants to the problems and the solutions in the area of the visual exploration of abstract data, with a particular emphasis on the visual perception phenomena, on the graphic metaphors that can be exploited and on thealgorithmic methods and models that can be adopted. The
knowledge of the participants about algorithm engineering and network optimization problems will be deepened. Such a knowledge will be applied to different strains of visualization problems with a strong practical approach.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
|
20802125 -
BIG DATA
(objectives)
The goal of the course is to illustrate the modern solutions to the management of big data, very large repositories of de-structured data. Starting from the requirements of modern database applications, the course will illustrate the hardware and software architectures that have been recently proposed for the management and analysis of big data. The topics addressed in the course will include: cluster architectures, map-reduce paradigm, cloud computing, NoSQL systems, tools and languages for data analysis. Both theoretical and practical aspects will be addressed and the discussed technologies will be experimented during practical classes and through the assignment of projects.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810288 -
12 CFU FREE OF THE STUDENT
(objectives)
The 12 credits of the student's free choice can be used to take exams by freely choosing from the exams offered by the University.
Some rules and some indications:
eligibility cannot be chosen
it is strongly recommended to include only exams offered by the Department of Engineering or check with the teacher of another department the availability of the activity
|
12
|
|
108
|
-
|
-
|
-
|
Elective activities
|
ITA |
Intelligenza artificiale e Machine Learning
FIRST YEAR
First semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20810256 -
Automata, Languages and Computing
(objectives)
Introduce the students to the theory of languages and, at the same time, to the theory of automata. introduce computability and complexity paradigms. At the end of the course students should know new formal methodologies, should be able to critically review, from the perspective of their expressive potential, already known methodologies and should be able to classify problems from the point of view of the resources required for their solution.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20801730 -
ARTIFICIAL INTELLIGENCE
(objectives)
The course aims to introduce advanced technologies of artificial intelligence, such as agent and multi-agent systems, probability-based reasoning, and the fundamentals of logic-based reasoning and decision support systems.
Developments in recent artificial intelligence models and technologies and their applications in the domains of major interest, such as robotics, AI-powered assistants, AI in education, finance, health-care and gaming, will be discussed.
The main and recent ethical, social and epistemological issues associated with the use of large-scale artificial intelligence tools and generative Artificial general intelligence will be discussed.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
Optional Group:
curriculum Intelligenza Artificiale e Machine Learning- I anno - due insegnamenti a scelta tra tre - (show)
|
18
|
|
|
|
|
|
|
|
|
20810007 -
Software Systems Architecture
(objectives)
The goal of the course is to present the discipline of software architecture, which is interested in studying the relationships between the structures of software systems and their quality attributes; this knowledge is fundamental for the analysis, design, evaluation and evolution of complex software systems. The course also presents the architecture of distributed software systems, the service-based architecture, and the software architecture for the Cloud, as well as some middleware services.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810259 -
Internet and Data Centers
(objectives)
The purpose is to provide advanced knowledge on computer networks and data centers, with methodological and technical contents. Special attention is devoted to scalability issues. At the end of the course the student is supposed to get the following concepts: inter-domain and intra-domain routing, congestion control, architectures for scalable systems. The student is also supposed to get advanced technicalities on widely adopted protocols. Finally, the student is supposed to understand the main economic and technical drivers of the internet and data centers evolution.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810260 -
Tecnologie e Architetture per la Gestione dei Dati
|
Also available in another semester or year
|
|
|
Optional Group:
curriculum Intelligenza Artificiale e Machine Learning- I anno - due insegnamenti a scelta tra sei - (show)
|
12
|
|
|
|
|
|
|
|
|
20802061 -
MULTIMEDIA LABORATORY
|
Also available in another semester or year
|
|
20801648 -
PROBABILITY AND STATISTICS
|
Also available in another semester or year
|
|
20810326 -
WIRELINE AND WIRELESS NETWORKS
(objectives)
The course describes the main characteristics and performance of wireline and wireless communication systems and networks: the physical layer features, data link protocols, switching techniques, medium access and data protection are described. The main architectures, technologies and protocols are described, that are used in fiber optic transport and access networks, 4G and 5G mobile networks, wireless local area networks (WLANs) and Internet of Things (IoT) networks.
|
6
|
ING-INF/03
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810252 -
MODELS AND ALGORITHMS FOR OPTIMIZATION
(objectives)
The course aims at providing basic methodological and operative knowledge to represent and cope with decision processes and quantitative models.
|
6
|
MAT/09
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810267 -
Artificial Intelligence from Engineering to Arts
|
Also available in another semester or year
|
|
20810208 -
Decision Support Systems and Analytics
(objectives)
The aim of the course is to present the main theoretical and methodological tools for modeling decisions and for identifying the best decision support strategies. The course also aims at providing the skills on how to use the available data in analytical prescriptive models, how to read the results provided by the adopted models and how to interpret them to propose appropriate solutions to complex management problems.
|
6
|
MAT/09
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
Second semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20810266 -
Machine Learning
(objectives)
The course aims to provide advanced and specific competencies in recent machine learning models and technologies. The course will enable the solving of complex problems through appropriate problem formulation and definition of the most suitable models and knowledge representations, and the most efficient implementation techniques for machine learning algorithms. Reinforcement learning and state-of-the-art models, such as graph neural networks and tuning and self-tuning techniques, will be introduced.
The course consists of a theoretical and methodological part on advanced and innovative concepts, and a laboratory activity in which these concepts are applied in problem solving using the latest development frameworks.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
Optional Group:
curriculum Intelligenza Artificiale e Machine Learning- I anno - due insegnamenti a scelta tra tre - (show)
|
18
|
|
|
|
|
|
|
|
|
20810007 -
Software Systems Architecture
|
Also available in another semester or year
|
|
20810259 -
Internet and Data Centers
|
Also available in another semester or year
|
|
20810260 -
Tecnologie e Architetture per la Gestione dei Dati
(objectives)
The goal of the course is to present models, methods and systems that play a fundamental role in database technology, together with discussions on the recent evolution of the technology itself. The directions of development to be considered include integration of heterogeneous and autonomous systems; databases for business intelligence and decision support. After taking the course, the student will know the major features of relational database technology, the methods for data integration, and for the design of data warehouses.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
|
Optional Group:
curriculum Intelligenza Artificiale e Machine Learning- I anno - due insegnamenti a scelta tra sei - (show)
|
12
|
|
|
|
|
|
|
|
|
20802061 -
MULTIMEDIA LABORATORY
(objectives)
The course aims at illustrating the more recent techniques for multimedia signal processing. Video signals and images will be analyzed in both bi-dimensional and tri-dimensional case. The course will be organized in two parts: in the first, the basics needed for multimedia signal processing and programming in Matlab will be presented to the students. In the second part practical experiences will be performed, both in individual and in group assignments, by using the tools available in the lab (Kinect, rendering 3D systems, stereo webcam). The possibility to use in the lab systems for acquiring, elaborating and rendering multimedia content, will allow the students to efficiently project and manage a multimedia system. The course will include dedicated seminars on practical applications of multimedia signals such as e-learning, cinema, IP-tv and mobile communications.
|
6
|
ING-INF/03
|
42
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20801648 -
PROBABILITY AND STATISTICS
(objectives)
To provide the fundamental elements of probability theory and mathematical statistics, along with some tools of parametric statistics, which may be useful in practice.
|
6
|
MAT/06
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810326 -
WIRELINE AND WIRELESS NETWORKS
|
Also available in another semester or year
|
|
20810252 -
MODELS AND ALGORITHMS FOR OPTIMIZATION
|
Also available in another semester or year
|
|
20810267 -
Artificial Intelligence from Engineering to Arts
(objectives)
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.
|
6
|
ING-IND/31
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810208 -
Decision Support Systems and Analytics
|
Also available in another semester or year
|
|
SECOND YEAR
First semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
Optional Group:
curriculum Intelligenza Artificiale e Machine Learning- II anno - due insegnamenti "a scelta tra" - (show)
|
12
|
|
|
|
|
|
|
|
|
20810006 -
ADVANCED TOPICS IN COMPUTER SCIENCE
|
Also available in another semester or year
|
|
20802125 -
BIG DATA
|
Also available in another semester or year
|
|
20802136 -
CYBER PHYSICAL SYSTEMS
(objectives)
The design of Cyber-Physical Systems (CPS) requires multi-disciplinary skills. In particular, the combined knowledge of various disciplines such as, control theory, signal processing, fault detection, and real-time computing, is crucial for the effective developments of CPS. Consequently, the course aims at providing to the students basics on such thematic areas considering a system-oriented approach. Moreover, also innovative methodologies for fault diagnosis and protection of CPS will be discussed considering the direct study of advanced research papers.
|
6
|
ING-INF/04
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810205 -
Digital entrepreneurship
|
Also available in another semester or year
|
|
20810223 -
DATA ENGINEERING
(objectives)
Providing skills on systems, methods, and technologies for extraction, cleaning, analyzing and integrating and management of unstructured data.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810264 -
Pianificazione Automatica
|
Also available in another semester or year
|
|
20810140 -
CYBERSECURITY
(objectives)
The Cybersecurity course intends to provide the student with competencies needed for understanding and tackling cybersecurity problems for ICT systems and complex organizations, to design networks and computing systems with a certain level of security, and to planning e manage activities related to cybersecurity. The course provides competences about attacks, countermeasures, cryptographic tools, applications, and methodologies in the cybersecurity field. Advanced topics in data integrity are also addressed.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810263 -
Logica
(objectives)
The course aims at giving basic knowledge of classical and some non-classical logics, their formal semantics and proof systems. Students will acquire the capability to use the studied logics for representation purposes and will be presented with some important applications of logic in computer science.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
|
20810262 -
Deep Learning
(objectives)
The course aims to provide advanced and specific skills in the area of the latest Deep neural network architectures. Particular attention will be given to multimodal models, and networks capable of analyzing complex data structures, such as graphs and multivariate time series; and deep reinforcement learning. At the end of the course, the student will be able to: adequately design and optimize Deep neural networks, be able to distinguish and evaluate different solutions, and be able to select and customize the most effective network architectures to be used in real application domains, supervised, unsupervised, or following a reinforcement learning approach. The course consists of a theoretical and methodological part on advanced and innovative concepts, and a laboratory activity in which these concepts are applied in problem solving using the latest development frameworks.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20801785 -
SKILLS FOR THE WORLD OF WORK
|
Also available in another semester or year
|
Second semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20801798 -
INTELLIGENT SYSTEMS FOR THE INTERNET
(objectives)
The course will allow students to learn various methods for the design, implementation, and testing of adaptive systems on the Web, created through Artificial Intelligence techniques, with particular reference to Machine Learning techniques. Specific attention will be paid to Information Retrieval systems, such as search engines, crawlers and document feeds. Classic retrieval models will be studied, such as the Vector Space Model and probabilistic models, document ranking techniques, as well as the PageRank algorithm used by Google. Machine Learning methods in Information Retrieval will be addressed, including techniques for Sentiment Analysis, User Modeling methods necessary for personalized search, and social search applications involving communities of individuals in activities such as content tagging and question answering. The techniques for analyzing social networks (e.g., Facebook and Twitter) will be explored, which will allow us to explore phenomena such as the spread of fake news, the filter bubble, and the polarization of users. Finally, Recommender Systems will be studied, from basic algorithms (e.g., collaborative filtering) to application scenarios (e.g., movies, books, music artists and songs).
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20801785 -
SKILLS FOR THE WORLD OF WORK
(objectives)
Frequency seminars mandatory.
The course aims to present the main soft skills for employment access through seminars held by speakers from the production reality. The seminaris illustrate the job and career dynamics in different types of companies (startups, SMEs, multinationals) in different sectors (software integrators, service companies, product companies, insurance and banking groups, utilities). Soft skills include how to write an effective CV, how to address the job interview. The course also introduces basic notions of labor laws.
|
1
|
|
25
|
-
|
-
|
-
|
Other activities
|
ITA |
|
20802019 -
FINAL EXAM
(objectives)
https://ingegneria.uniroma3.it/didattica/collegio-informatica/lauree-e-tirocini/laurea-magistrale/
|
26
|
|
650
|
-
|
-
|
-
|
Final examination and foreign language test
|
ITA |
|
Optional Group:
curriculum Intelligenza Artificiale e Machine Learning- II anno - due insegnamenti "a scelta tra" - (show)
|
12
|
|
|
|
|
|
|
|
|
20810006 -
ADVANCED TOPICS IN COMPUTER SCIENCE
(objectives)
The goal of the course is to present models, methods and systems related to the latest advances in the field of information technology able to meet the requirements of modern applications. The course is taught in English by foreign professors of high qualification
|
6
|
ING-INF/05
|
42
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20802125 -
BIG DATA
(objectives)
The goal of the course is to illustrate the modern solutions to the management of big data, very large repositories of de-structured data. Starting from the requirements of modern database applications, the course will illustrate the hardware and software architectures that have been recently proposed for the management and analysis of big data. The topics addressed in the course will include: cluster architectures, map-reduce paradigm, cloud computing, NoSQL systems, tools and languages for data analysis. Both theoretical and practical aspects will be addressed and the discussed technologies will be experimented during practical classes and through the assignment of projects.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20802136 -
CYBER PHYSICAL SYSTEMS
|
Also available in another semester or year
|
|
20810205 -
Digital entrepreneurship
(objectives)
Provide students with technical and methodological skills
necessary to conceive, develop and implement a digital business project.
The course will be divided into three parts. The first part aims to explain the reasons behind the success of digital companies (especially, but not only, startups) and digital innovation dynamics. The second part offers students the technical and methodological tools for the realization of a digital business project. The third part consists in the realization of a project and is characterized by a strongly experimental approach.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810223 -
DATA ENGINEERING
|
Also available in another semester or year
|
|
20810264 -
Pianificazione Automatica
(objectives)
The course presents Artificial Intelligence planning problems. It introduces models and resolution techniques for both "classic" and temporal planning, involving scheduling aspects. Different methodologies for the synthesis of action plans and their execution will be presented, as well as aspects related to automated learning of classical planning domains. Furthermore, some applications and samples will be presented and discussed, also in relation to the control of autonomous robots
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810140 -
CYBERSECURITY
|
Also available in another semester or year
|
|
20810263 -
Logica
|
Also available in another semester or year
|
|
|
20810288 -
12 CFU FREE OF THE STUDENT
(objectives)
The 12 credits of the student's free choice can be used to take exams by freely choosing from the exams offered by the University.
Some rules and some indications:
eligibility cannot be chosen
it is strongly recommended to include only exams offered by the Department of Engineering or check with the teacher of another department the availability of the activity
|
12
|
|
108
|
-
|
-
|
-
|
Elective activities
|
ITA |
Algoritmi, Big Data e Machine Learning
FIRST YEAR
First semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20810256 -
Automata, Languages and Computing
(objectives)
Introduce the students to the theory of languages and, at the same time, to the theory of automata. introduce computability and complexity paradigms. At the end of the course students should know new formal methodologies, should be able to critically review, from the perspective of their expressive potential, already known methodologies and should be able to classify problems from the point of view of the resources required for their solution.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810259 -
Internet and Data Centers
(objectives)
The purpose is to provide advanced knowledge on computer networks and data centers, with methodological and technical contents. Special attention is devoted to scalability issues. At the end of the course the student is supposed to get the following concepts: inter-domain and intra-domain routing, congestion control, architectures for scalable systems. The student is also supposed to get advanced technicalities on widely adopted protocols. Finally, the student is supposed to understand the main economic and technical drivers of the internet and data centers evolution.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
Optional Group:
curriculum Sistemi Informatici Complessi - curriculum ingegneria dei Dati- curriculum Algoritmi, Big Data e Machine Learning-I ANNO due insegnamenti a scelta tra cinque - (show)
|
12
|
|
|
|
|
|
|
|
|
20810252 -
MODELS AND ALGORITHMS FOR OPTIMIZATION
(objectives)
The course aims at providing basic methodological and operative knowledge to represent and cope with decision processes and quantitative models.
|
6
|
MAT/09
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810208 -
Decision Support Systems and Analytics
(objectives)
The aim of the course is to present the main theoretical and methodological tools for modeling decisions and for identifying the best decision support strategies. The course also aims at providing the skills on how to use the available data in analytical prescriptive models, how to read the results provided by the adopted models and how to interpret them to propose appropriate solutions to complex management problems.
|
6
|
MAT/09
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810257 -
Diritto dei Dati
|
Also available in another semester or year
|
|
20801648 -
PROBABILITY AND STATISTICS
|
Also available in another semester or year
|
|
20810326 -
WIRELINE AND WIRELESS NETWORKS
(objectives)
The course describes the main characteristics and performance of wireline and wireless communication systems and networks: the physical layer features, data link protocols, switching techniques, medium access and data protection are described. The main architectures, technologies and protocols are described, that are used in fiber optic transport and access networks, 4G and 5G mobile networks, wireless local area networks (WLANs) and Internet of Things (IoT) networks.
|
6
|
ING-INF/03
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
|
Optional Group:
curriculum Algoritmi, Big Data e Machine Learning- I anno un insegnamento a scelta tra due - (show)
|
9
|
|
|
|
|
|
|
|
|
20810007 -
Software Systems Architecture
(objectives)
The goal of the course is to present the discipline of software architecture, which is interested in studying the relationships between the structures of software systems and their quality attributes; this knowledge is fundamental for the analysis, design, evaluation and evolution of complex software systems. The course also presents the architecture of distributed software systems, the service-based architecture, and the software architecture for the Cloud, as well as some middleware services.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20801730 -
ARTIFICIAL INTELLIGENCE
(objectives)
The course aims to introduce advanced technologies of artificial intelligence, such as agent and multi-agent systems, probability-based reasoning, and the fundamentals of logic-based reasoning and decision support systems.
Developments in recent artificial intelligence models and technologies and their applications in the domains of major interest, such as robotics, AI-powered assistants, AI in education, finance, health-care and gaming, will be discussed.
The main and recent ethical, social and epistemological issues associated with the use of large-scale artificial intelligence tools and generative Artificial general intelligence will be discussed.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
Second semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20810266 -
Machine Learning
(objectives)
The course aims to provide advanced and specific competencies in recent machine learning models and technologies. The course will enable the solving of complex problems through appropriate problem formulation and definition of the most suitable models and knowledge representations, and the most efficient implementation techniques for machine learning algorithms. Reinforcement learning and state-of-the-art models, such as graph neural networks and tuning and self-tuning techniques, will be introduced.
The course consists of a theoretical and methodological part on advanced and innovative concepts, and a laboratory activity in which these concepts are applied in problem solving using the latest development frameworks.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810260 -
Tecnologie e Architetture per la Gestione dei Dati
(objectives)
The goal of the course is to present models, methods and systems that play a fundamental role in database technology, together with discussions on the recent evolution of the technology itself. The directions of development to be considered include integration of heterogeneous and autonomous systems; databases for business intelligence and decision support. After taking the course, the student will know the major features of relational database technology, the methods for data integration, and for the design of data warehouses.
|
9
|
ING-INF/05
|
81
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
Optional Group:
curriculum Sistemi Informatici Complessi - curriculum ingegneria dei Dati- curriculum Algoritmi, Big Data e Machine Learning-I ANNO due insegnamenti a scelta tra cinque - (show)
|
12
|
|
|
|
|
|
|
|
|
20810252 -
MODELS AND ALGORITHMS FOR OPTIMIZATION
|
Also available in another semester or year
|
|
20810208 -
Decision Support Systems and Analytics
|
Also available in another semester or year
|
|
20810257 -
Diritto dei Dati
(objectives)
Provide an introduction to the main principles and rules concerning data governance under Italian and European law. Study the legal distinction between personal and non personal data, with reference to the main instruments related to property, access, and circulation of data (intellectual property, trade secret, personal data protection). Analyse the issues deriving from the use of data in algorithmic decisions, both in administrative and private law contexts.
|
6
|
IUS/02
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20801648 -
PROBABILITY AND STATISTICS
(objectives)
To provide the fundamental elements of probability theory and mathematical statistics, along with some tools of parametric statistics, which may be useful in practice.
|
6
|
MAT/06
|
54
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
20810326 -
WIRELINE AND WIRELESS NETWORKS
|
Also available in another semester or year
|
|
|
Optional Group:
curriculum Algoritmi, Big Data e Machine Learning- I anno un insegnamento a scelta tra due - (show)
|
9
|
|
|
|
|
|
|
|
|
SECOND YEAR
First semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
Optional Group:
Curriculum Algoritmi, Big Data e Machine Learning II anno- due insegnamenti a scelta tra di cui almeno uno: Cybersecurity, Visualizzazione delle Informazioni - (show)
|
12
|
|
|
|
|
|
|
|
|
20810006 -
ADVANCED TOPICS IN COMPUTER SCIENCE
|
Also available in another semester or year
|
|
20810261 -
Computer Graphics
(objectives)
This course aims at illustrating the modern software and hardware computer graphics architectures, and at providing mathematical, technical and methodological solutions for the development of projects concerning the visualization of data in 2D or 3D. The course will expose base concepts in computer graphics such as spaces, curves, surfaces and volumes, focusing on notions and algorithms currently used in scientific visualization, videogames, and computer animation. Moreover, this course aims at exposing details of hardware and software platforms currently in use.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810140 -
CYBERSECURITY
(objectives)
The Cybersecurity course intends to provide the student with competencies needed for understanding and tackling cybersecurity problems for ICT systems and complex organizations, to design networks and computing systems with a certain level of security, and to planning e manage activities related to cybersecurity. The course provides competences about attacks, countermeasures, cryptographic tools, applications, and methodologies in the cybersecurity field. Advanced topics in data integrity are also addressed.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810262 -
Deep Learning
(objectives)
The course aims to provide advanced and specific skills in the area of the latest Deep neural network architectures. Particular attention will be given to multimodal models, and networks capable of analyzing complex data structures, such as graphs and multivariate time series; and deep reinforcement learning. At the end of the course, the student will be able to: adequately design and optimize Deep neural networks, be able to distinguish and evaluate different solutions, and be able to select and customize the most effective network architectures to be used in real application domains, supervised, unsupervised, or following a reinforcement learning approach. The course consists of a theoretical and methodological part on advanced and innovative concepts, and a laboratory activity in which these concepts are applied in problem solving using the latest development frameworks.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810205 -
Digital entrepreneurship
|
Also available in another semester or year
|
|
20810223 -
DATA ENGINEERING
(objectives)
Providing skills on systems, methods, and technologies for extraction, cleaning, analyzing and integrating and management of unstructured data.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20801798 -
INTELLIGENT SYSTEMS FOR THE INTERNET
|
Also available in another semester or year
|
|
20802126 -
INFORMATION VISUALIZATION
|
Also available in another semester or year
|
|
|
20810211 -
Algorithms for big data
(objectives)
In many application contexts huge volumes of data are produced which are
used in the economic-financial, political, social and even institutional
fields. Often the data is stored in huge distributed clouds and is
sometimes generated according to a continuous flow, so large as to make
complete storage unfeasible. In many cases the data pertains to entities
in close relationship with each other and gives rise to massive networks
of connections. Familiar examples for such networks are biological and
social networks, distribution networks, and the Web graph. Furthermore,
the fact that the data is stored in systems managed by third parties
poses integrity problems, which have not been considered in the
classical IT literature in terms of both their type and scale.
This scenario poses unprecedented algorithmic challenges, which are
being considered by a vast audience of researchers. In the last decade,
this effort has produced many innovations on both the methodological and
technological level. This course aims at transferring to the students
some of the most important methodological tools originated from the
research on Big Data algorithms. These methodological tools are
presented within challenging application contexts.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20801785 -
SKILLS FOR THE WORLD OF WORK
|
Also available in another semester or year
|
Second semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
20801785 -
SKILLS FOR THE WORLD OF WORK
(objectives)
Frequency seminars mandatory.
The course aims to present the main soft skills for employment access through seminars held by speakers from the production reality. The seminaris illustrate the job and career dynamics in different types of companies (startups, SMEs, multinationals) in different sectors (software integrators, service companies, product companies, insurance and banking groups, utilities). Soft skills include how to write an effective CV, how to address the job interview. The course also introduces basic notions of labor laws.
|
1
|
|
25
|
-
|
-
|
-
|
Other activities
|
ITA |
|
20802019 -
FINAL EXAM
(objectives)
https://ingegneria.uniroma3.it/didattica/collegio-informatica/lauree-e-tirocini/laurea-magistrale/
|
26
|
|
650
|
-
|
-
|
-
|
Final examination and foreign language test
|
ITA |
|
20802125 -
BIG DATA
(objectives)
The goal of the course is to illustrate the modern solutions to the management of big data, very large repositories of de-structured data. Starting from the requirements of modern database applications, the course will illustrate the hardware and software architectures that have been recently proposed for the management and analysis of big data. The topics addressed in the course will include: cluster architectures, map-reduce paradigm, cloud computing, NoSQL systems, tools and languages for data analysis. Both theoretical and practical aspects will be addressed and the discussed technologies will be experimented during practical classes and through the assignment of projects.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
Optional Group:
Curriculum Algoritmi, Big Data e Machine Learning II anno- due insegnamenti a scelta tra di cui almeno uno: Cybersecurity, Visualizzazione delle Informazioni - (show)
|
12
|
|
|
|
|
|
|
|
|
20810006 -
ADVANCED TOPICS IN COMPUTER SCIENCE
(objectives)
The goal of the course is to present models, methods and systems related to the latest advances in the field of information technology able to meet the requirements of modern applications. The course is taught in English by foreign professors of high qualification
|
6
|
ING-INF/05
|
42
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810261 -
Computer Graphics
|
Also available in another semester or year
|
|
20810140 -
CYBERSECURITY
|
Also available in another semester or year
|
|
20810262 -
Deep Learning
|
Also available in another semester or year
|
|
20810205 -
Digital entrepreneurship
(objectives)
Provide students with technical and methodological skills
necessary to conceive, develop and implement a digital business project.
The course will be divided into three parts. The first part aims to explain the reasons behind the success of digital companies (especially, but not only, startups) and digital innovation dynamics. The second part offers students the technical and methodological tools for the realization of a digital business project. The third part consists in the realization of a project and is characterized by a strongly experimental approach.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20810223 -
DATA ENGINEERING
|
Also available in another semester or year
|
|
20801798 -
INTELLIGENT SYSTEMS FOR THE INTERNET
(objectives)
The course will allow students to learn various methods for the design, implementation, and testing of adaptive systems on the Web, created through Artificial Intelligence techniques, with particular reference to Machine Learning techniques. Specific attention will be paid to Information Retrieval systems, such as search engines, crawlers and document feeds. Classic retrieval models will be studied, such as the Vector Space Model and probabilistic models, document ranking techniques, as well as the PageRank algorithm used by Google. Machine Learning methods in Information Retrieval will be addressed, including techniques for Sentiment Analysis, User Modeling methods necessary for personalized search, and social search applications involving communities of individuals in activities such as content tagging and question answering. The techniques for analyzing social networks (e.g., Facebook and Twitter) will be explored, which will allow us to explore phenomena such as the spread of fake news, the filter bubble, and the polarization of users. Finally, Recommender Systems will be studied, from basic algorithms (e.g., collaborative filtering) to application scenarios (e.g., movies, books, music artists and songs).
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
20802126 -
INFORMATION VISUALIZATION
(objectives)
The goal of this course is that of introducing the participants to the problems and the solutions in the area of the visual exploration of abstract data, with a particular emphasis on the visual perception phenomena, on the graphic metaphors that can be exploited and on thealgorithmic methods and models that can be adopted. The
knowledge of the participants about algorithm engineering and network optimization problems will be deepened. Such a knowledge will be applied to different strains of visualization problems with a strong practical approach.
|
6
|
ING-INF/05
|
54
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
|
20810288 -
12 CFU FREE OF THE STUDENT
(objectives)
The 12 credits of the student's free choice can be used to take exams by freely choosing from the exams offered by the University.
Some rules and some indications:
eligibility cannot be chosen
it is strongly recommended to include only exams offered by the Department of Engineering or check with the teacher of another department the availability of the activity
|
12
|
|
108
|
-
|
-
|
-
|
Elective activities
|
ITA |
Università Roma Tre