Corso di Laurea Magistrale in Ingegneria Informatica

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1 Corso di Laurea Magistrale in Ingegneria Informatica Siti web: corsidilaurea.uniroma1.it/it/corso/2017/ingegneria-informatica/ e cclii.dis.uniroma1.it

2 Ingegneria Informatica L'ingegneria informatica è la branca dell'ingegneria che si occupa dell'analisi,del progetto, dello sviluppo e della manutenzione dei sistemi per l'elaborazione dell'informazione L ingegnere informatico è un professionista che svolge attività di pianificazione, progettazione, realizzazione, gestione e esercizio di sistemie infrastruttureper la rappresentazione, la trasmissione e l'elaborazione delle informazioni MSc in Engineering in Computer Science

3 Laurea Magistrale MINR L obiettivo della laurea Magistrale in Ingegneria informatica Master of Science in Engineeringin Computer Science(MINR) è duplice: Completare la formazione dell ingegnere informatico attraverso lo studio di metodologie ed aspetti teorici. Introdurre lo studente ad argomenti specializzati anche attraverso lo studio dell attuale stato dell arte nei rispettivi ambiti di ricerca Il corso di laurea forma persone per: Inserimento diretto nel mondo del lavoro Specializzazione in corsi di formazione avanzata Dottorato di ricerca Master di 2 livello MSc in Engineering in Computer Science

4 Laurea Magistrale Scuola superiore Laurea triennale Laurea magistrale Dottorato 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 informatica è un settore ad altissimo livello di internazionalizzazione Capacità degli studenti spendibili in un contesto internazionale Contribuire alla competitività delle aziende Italiane Attrarre giovani talenti da altri paesi Ma funziona? 5 anni di esperienza con un doppio canale + 5 anni solo inglese Alto grado di internazionalizzazione dei docenti Lezioni erogate anche da docenti stranieri MSc in Engineering in Computer Science

6 Insegnamenti obbligatori (30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Artificial Intelligence I oppure Machine Learning (6cfu) MINR: Struttura del Curriculum Idoneità obbligatorie (6cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) 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 Insegnamenti a scelta dello studente (12cfu) Tesi e prova finale (30cfu) Algorithms Insegnamenti 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 Microcontroller System Design Pervasive Systems System Enterprise Security

7 Esempio Percorso: Data and Information Management Insegnamenti obbligatori(30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Artificial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatorie(9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) 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 Insegnamenti a scelta dello studente(12cfu) Tesi e prova finale (30cfu) Algorithms Insegnamenti 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 Microcontroller System Design Pervasive Systems System Enterprise Security

8 Esempio Percorso: Big Data Analytics Technologies Insegnamenti obbligatori(30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Artificial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatorie(9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) 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 Insegnamenti a scelta dello studente(12cfu) Optimization Methods in Machine Learning Stochastic Processes in Data Science (MSc. Data Science) Tesi e prova finale (30cfu) Algorithms Insegnamenti 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 Microcontroller System Design Pervasive Systems System Enterprise Security

9 Esempio Percorso: Software and Application Development Insegnamenti obbligatori(30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Artificial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatorie(9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) 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 Insegnamenti a scelta dello studente(12cfu) Tesi e prova finale (30cfu) Algorithms Insegnamenti 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 Microcontroller System Design Pervasive Systems System Enterprise Security

10 Esempio Percorso: Cloud Computing Insegnamenti obbligatori(30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Artificial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatorie(9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) 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 Insegnamenti a scelta dello studente(12cfu) Tesi e prova finale (30cfu) Algorithms Insegnamenti 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 Microcontroller System Design Pervasive Systems System Enterprise Security

11 Esempio Percorso: Cyber Security Technologies Insegnamenti obbligatori(30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Artificial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatore(9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) 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 Insegnamenti a scelta dello studente(12cfu) Corsi da MSc in Cyber Security Tesi e prova finale (30cfu) Algorithms Insegnamenti 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 Microcontroller System Design Pervasive Systems System Enterprise Security

12 Esempio perc.: Smart Environments and Internet of Things Insegnamenti obbligatori(30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Artificial Intelligence I oppure Machine Learning (6cfu) Idoneità obbligatore(9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) 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 Insegnamenti a scelta dello studente(12cfu): Product Design Studio 3 (12cfu) da MSc. Product Design (Architettura) Tesi e prova finale (30cfu) Algorithms Insegnamenti 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 Microcontroller System Design Pervasive Systems System Enterprise Security

13 Esempio Percorso: Artificial Intelligence Technologies Insegnamenti obbligatori(30cfu): Advanced Programming (6cfu) Algorithm Design (6cfu) Data Management (6cfu) Distributed Systems and Computer and Network Security (12cfu) Artificial Intelligence I oppure Machine Learning (6cfu) Insegnamenti obbligatori idoneita(9cfu): Seminars in Advanced Topics in Computer Science Engineering (6cfu) 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 Insegnamenti a scelta dello studente(12cfu) Tesi e prova finale (30cfu) Algorithms Insegnamenti 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 Microcontroller System Design Pervasive Systems System Enterprise Security Insegnamenti presi da MARR: Artificial Intelligence I+II (12cfu) Planning and Reasoning Vision and Perception

14 Erasmus Programma Erasmus MSc in Engineering in Computer Science

15 Percorso di eccellenza Ha lo scopo di valorizzare la formazione degli studenti meritevoli ed interessati ad attività di approfondimento scientifico. Consiste in Attività formative aggiuntive Seminari Corsi per studenti di dottorato Integrazione con i gruppi di ricerca nell ambito di attività scientifiche Possono richiedere l'accesso al percorso di eccellenza gli studenti che al termine del primo anno di corso abbiano acquisito almeno 40 crediti formativi universitari (CFU) con media non inferiore a 27/30. Il numero massimo di studenti ammessi al percorso di eccellenza è 10. MSc in Engineering in Computer Science

16 Ambiente stimolante Sede prevalente dei corsi è il palazzo del DIAG Strutture disponibili: Aule attrezzate Biblioteca Aule per tesisti Laboratori di ricerca Coinvolgimento degli studenti in attività collaterali Seminari Conferenze organizzate nella struttura Eventi MSc in Engineering in Computer Science

17 Questions? MSc in Engineering in Computer Science