Corso di Laurea Magistrale in Ingegneria Informa4ca.

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1 Corso di Laurea Magistrale in Ingegneria Informa4ca

2 Ingegneria Informa,ca L'ingegneria informa4ca è la branca dell'ingegneria che si occupa dell'analisi, del proge9o, dello sviluppo e della manutenzione dei sistemi per l'elaborazione dell'informazione L ingegnere informa4co è un professionista che svolge a>vità di pianificazione, proge9azione, realizzazione, ges,one e esercizio di sistemi e infrastru9ure per la rappresentazione, la trasmissione e l'elaborazione delle informazioni MSc in Engineering in Computer Science

3 Laurea Magistrale MINR L obie>vo della laurea Magistrale in Ingegneria informa,ca Master of Science in Engineering in Computer Science (MINR) è duplice: Completare la formazione dell ingegnere informa,co a9raverso lo studio di metodologie ed aspe> teorici. Introdurre lo studente ad argomen, specializza, anche a9raverso lo studio dell a9uale stato dell arte nei rispe>vi ambi, di ricerca Il corso di laurea forma persone per: Inserimento dire9o nel mondo del lavoro Specializzazione in corsi di formazione avanzata Do9orato di ricerca Master di 2 livello MSc in Engineering in Computer Science

4 Laurea Magistrale Scuola superiore Laurea triennale Laurea magistrale Do9orato Master 1 livello Master 2 livello Mondo del lavoro MSc in Engineering in Computer Science

5 MINR in Inglese! Il corso di laurea MINR è erogato completamente in Inglese Perché? L ingegneria informa,ca è un se9ore ad al,ssimo livello di internazionalizzazione Capacità degli studen, spendibili in un contesto internazionale Contribuire alla compe,,vità delle aziende Italiane A9rarre giovani talen, da altri paesi Ma funziona? 5 anni di esperienza con un doppio canale + 5 anni solo inglese Alto grado di internazionalizzazione dei docen, Lezioni erogate anche da docen, stranieri MSc in Engineering in Computer Science

6 Insegnamen4 obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Ar,ficial Intelligence I oppure Machine Learning (6cfu) MINR: Stru9ura del Curriculum Idoneità obbligatorie (9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) Lingua Inglese (3cfu) Insegnamenti ingegneristici (almeno 6 cfu): Network Infrastructure ING-INF/03 Embedded Systems ING-INF/03 Neural Networks ING-IND/31 Natural Language Processing INF/01 Network Traffic Engineering ING-INF/03 Control of Communication and Energy Networks ING-INF/04 Laboratory of Network Design and Configuration MARR Insegnamen4 a scelta dello studente (12cfu) Tesi e prova finale (27cfu) Algorithms Insegnamen4 opzionali (36cfu) Big Data Computing Data Mining Probabilistic Methods for the Analysis of Experimental Data Social Networks and On-line Markets Data Management Knowledge Representation and Semantic Technologies Large-Scale Data Management Visual Analytics Software Engineering Formal Methods Software Engineering Human Computer Interaction Process and Service Modeling and Analysis Software Applications Mobile Applications and Cloud Computing Web Information Retrieval Web Security and Privacy Systems Advanced Operating Systems and Virtualization Capacity Planning Data Centers and High Performance Computing Pervasive Systems System Enterprise Security

7 Esempio Percorso: Data and Informa4on Management Insegnamen4 obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Ar4ficial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatorie (9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) Lingua Inglese (3cfu) Insegnamenti ingegneristici (almeno 6 cfu): Network Infrastructure ING-INF/03 Embedded Systems ING-INF/03 Neural Networks ING-IND/31 Natural Language Processing INF/01 Network Traffic Engineering ING-INF/03 Control of Communication and Energy Networks ING-INF/04 Laboratory of Network Design and Configuration MARR Insegnamen4 a scelta dello studente (12cfu) Tesi e prova finale (27cfu) Algorithms Insegnamen4 opzionali (36cfu) Big Data Computing Data Mining Probabilistic Methods for the Analysis of Experimental Data Social Networks and On-line Markets Data Management Knowledge Representation and Semantic Technologies Large-Scale Data Management Visual Analytics Software Engineering Formal Methods Software Engineering Human Computer Interaction Process and Service Modeling and Analysis Software Applications Mobile Applications and Cloud Computing Web Information Retrieval Web Security and Privacy Systems Advanced Operating Systems and Virtualization Capacity Planning Data Centers and High Performance Computing Pervasive Systems System Enterprise Security

8 Esempio Percorso: Big Data Analy4cs Technologies Insegnamen4 obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Ar,ficial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatorie (9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) Lingua Inglese (3cfu) Insegnamenti ingegneristici (almeno 6 cfu): Network Infrastructure ING-INF/03 Embedded Systems ING-INF/03 Neural Networks ING-IND/31 Natural Language Processing INF/01 Network Traffic Engineering ING-INF/03 Control of Communication and Energy Networks ING-INF/04 Laboratory of Network Design and Configuration MARR Insegnamen4 a scelta dello studente (12cfu) Op4miza4on Methods in Machine Learning Stochas4c Processes in Data Science (MSc. Data Science) Tesi e prova finale (27cfu) Algorithms Insegnamen4 opzionali (36cfu) Big Data Computing Data Mining Probabilistic Methods for the Analysis of Experimental Data Social Networks and On-line Markets Data Management Knowledge Representation and Semantic Technologies Large-Scale Data Management Visual Analytics Software Engineering Formal Methods Software Engineering Human Computer Interaction Process and Service Modeling and Analysis Software Applications Mobile Applications and Cloud Computing Web Information Retrieval Web Security and Privacy Systems Advanced Operating Systems and Virtualization Capacity Planning Data Centers and High Performance Computing Pervasive Systems System Enterprise Security

9 Esempio Percorso: SoTware and Applica4on Development Insegnamen4 obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Ar4ficial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatorie (9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) Lingua Inglese (3cfu) Insegnamenti ingegneristici (almeno 6 cfu): Network Infrastructure ING-INF/03 Embedded Systems ING-INF/03 Neural Networks ING-IND/31 Natural Language Processing INF/01 Network Traffic Engineering ING-INF/03 Control of Communication and Energy Networks ING-INF/04 Laboratory of Network Design and Configuration MARR Insegnamen4 a scelta dello studente (12cfu) Tesi e prova finale (27cfu) Algorithms Insegnamen4 opzionali (36cfu) Big Data Computing Data Mining Probabilistic Methods for the Analysis of Experimental Data Social Networks and On-line Markets Data Management Knowledge Representation and Semantic Technologies Large-Scale Data Management Visual Analytics Software Engineering Formal Methods Software Engineering Human Computer Interaction Process and Service Modeling and Analysis Software Applications Mobile Applications and Cloud Computing Web Information Retrieval Web Security and Privacy Systems Advanced Operating Systems and Virtualization Capacity Planning Data Centers and High Performance Computing Pervasive Systems System Enterprise Security

10 Esempio Percorso: Cloud Compu4ng Insegnamen4 obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Ar,ficial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatorie (9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) Lingua Inglese (3cfu) Insegnamenti ingegneristici (almeno 6 cfu): Network Infrastructure ING-INF/03 Embedded Systems ING-INF/03 Neural Networks ING-IND/31 Natural Language Processing INF/01 Network Traffic Engineering ING-INF/03 Control of Communication and Energy Networks ING-INF/04 Laboratory of Network Design and Configuration MARR Insegnamen4 a scelta dello studente (12cfu) Tesi e prova finale (27cfu) Algorithms Insegnamen4 opzionali (36cfu) Big Data Computing Data Mining Probabilistic Methods for the Analysis of Experimental Data Social Networks and On-line Markets Data Management Knowledge Representation and Semantic Technologies Large-Scale Data Management Visual Analytics Software Engineering Formal Methods Software Engineering Human Computer Interaction Process and Service Modeling and Analysis Software Applications Mobile Applications and Cloud Computing Web Information Retrieval Web Security and Privacy Systems Advanced Operating Systems and Virtualization Capacity Planning Data Centers and High Perfor. Computing Pervasive Systems System Enterprise Security

11 Esempio Percorso: Edge Compu4ng Insegnamen4 obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Ar,ficial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatorie (9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) Lingua Inglese (3cfu) Insegnamenti ingegneristici (almeno 6 cfu): Network Infrastructure ING-INF/03 Embedded Systems ING-INF/03 Neural Networks ING-IND/31 Natural Language Processing INF/01 Network Traffic Engineering ING-INF/03 Control of Communication and Energy Networks ING-INF/04 Laboratory of Network Design and Configuration MARR Insegnamen4 a scelta dello studente (12cfu) Tesi e prova finale (27cfu) Algorithms Insegnamen4 opzionali (36cfu) Big Data Computing Data Mining Probabilistic Methods for the Analysis of Experimental Data Social Networks and On-line Markets Data Management Knowledge Representation and Semantic Technologies Large-Scale Data Management Visual Analytics Software Engineering Formal Methods Software Engineering Human Computer Interaction Process and Service Modeling and Analysis Software Applications Mobile Applications and Cloud Computing Web Information Retrieval Web Security and Privacy Systems Advanced Operating Systems and Virtualization Capacity Planning Data Centers and High Perfor. Computing Pervasive Systems System Enterprise Security

12 Esempio Percorso: Cyber Security Technologies Insegnamen4 obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Ar,ficial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatore (9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) Lingua Inglese (3cfu) Insegnamenti ingegneristici (almeno 6 cfu): Network Infrastructure ING-INF/03 Embedded Systems ING-INF/03 Neural Networks ING-IND/31 Natural Language Processing INF/01 Network Traffic Engineering ING-INF/03 Control of Communication and Energy Networks ING-INF/03 Laboratory of Network Design and Configuration MARR Insegnamen4 a scelta dello studente (12cfu) Corsi da MSc in Cyber Security Tesi e prova finale (27cfu) Algorithms Insegnamen4 opzionali (36cfu) Big Data Computing Data Mining Probabilistic Methods for the Analysis of Experimental Data Social Networks and On-line Markets Data Management Knowledge Representation and Semantic Technologies Large-Scale Data Management Visual Analytics Software Engineering Formal Methods Software Engineering Human Computer Interaction Process and Service Modeling and Analysis Software Applications Mobile Applications and Cloud Computing Web Information Retrieval Web Security and Privacy Systems Advanced Operating Systems and Virtualization Capacity Planning Data Centers and High Performance Computing Pervasive Systems System Enterprise Security

13 Esempio perc.: Smart Environments and Internet of Things Insegnamen4 obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Ar,ficial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatore (9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) Lingua Inglese (3cfu) Insegnamenti ingegneristici (almeno 6 cfu): Network Infrastructure ING-INF/03 Embedded Systems ING-INF/03 Neural Networks ING-IND/31 Natural Language Processing INF/01 Network Traffic Engineering ING-INF/03 Control of Communication and Energy Networks ING-INF/03 Laboratory of Network Design and Configuration MARR Insegnamen4 a scelta dello studente (12cfu): Product Design Studio 3 (12cfu) da MSc. Product Design (ArchiteUura) Tesi e prova finale (27cfu) Algorithms Insegnamen4 opzionali (36cfu) Big Data Computing Data Mining Probabilistic Methods for the Analysis of Experimental Data Social Networks and On-line Markets Data Management Knowledge Representation and Semantic Technologies Large-Scale Data Management Visual Analytics Software Engineering Formal Methods Software Engineering Human Computer Interaction Process and Service Modeling and Analysis Software Applications Mobile Applications and Cloud Computing Web Information Retrieval Web Security and Privacy Systems Advanced Operating Systems and Virtualization Capacity Planning Data Centers and High Performance Computing Pervasive Systems System Enterprise Security

14 Esempio Percorso: Ar4ficial Intelligence Technologies Insegnamen4 obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Ar,ficial Intelligence I oppure Machine Learning (6cfu) Insegnamen4 obbligatori idoneita (9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) Lingua Inglese (3cfu) Insegnamenti ingegneristici (almeno 6 cfu): Network Infrastructure ING-INF/03 Embedded Systems ING-INF/03 Neural Networks ING-IND/31 Natural Language Processing INF/01 Network Traffic Engineering ING-INF/03 Control of Communication and Energy Networks ING-INF/04 Laboratory of Network Design and Configuration MARR Insegnamen4 a scelta dello studente (12cfu) Tesi e prova finale (27cfu) Algorithms Insegnamen4 opzionali (36cfu) Big Data Computing Data Mining Probabilistic Methods for the Analysis of Experimental Data Social Networks and On-line Markets Data Management Knowledge Representation and Semantic Technologies Large-Scale Data Management Visual Analytics Software Engineering Formal Methods Software Engineering Human Computer Interaction Process and Service Modeling and Analysis Software Applications Mobile Applications and Cloud Computing Web Information Retrieval Web Security and Privacy Systems Advanced Operating Systems and Virtualization Capacity Planning Data Centers and High Perfor. Computing Pervasive Systems System Enterprise Security Insegnamenti presi da MARR: Artificial Intelligence I+II (12cfu) Planning and Reasoning Vision and Perception

15 Erasmus Programma Erasmus MSc in Engineering in Computer Science

16 Percorso di eccellenza Ha lo scopo di valorizzare la formazione degli studen, meritevoli ed interessa, ad a>vità di approfondimento scien,fico. Consiste in A>vità forma,ve aggiun,ve Seminari Corsi per studen, di do9orato Integrazione con i gruppi di ricerca nell ambito di a>vità scien,fiche Possono richiedere l'accesso al percorso di eccellenza gli studen, che al termine del primo anno di corso abbiano acquisito almeno 40 credi, forma,vi universitari (CFU) con media non inferiore a 27/30. Il numero massimo di studen, ammessi al percorso di eccellenza è 10. MSc in Engineering in Computer Science

17 Ambiente s,molante Sede prevalente dei corsi è il palazzo del DIAG Stru9ure disponibili: Aule a9rezzate Biblioteca Aule per tesis, Laboratori di ricerca Coinvolgimento degli studen, in a>vità collaterali Seminari Conferenze organizzate nella stru9ura Even, MSc in Engineering in Computer Science

18 Questions? MSc in Engineering in Computer Science