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9793927 -
IoT AND BIG DATA FOR SMART SPACES
(obiettivi)
Knowledge and Understanding: On completion of the course, the student shall 1) Know the key technological components underpinning IoT, 2) Understand IoT Architectures and the application of IoT in various domains, 3) Know the difference among networking protocols in the context of resource-constrained IoT devices, and 4) Know how Big Data can be exploited in the context of Smart Spaces.
Applying Knowledge and Understanding: On completion of the course, the student shall be able to analyze and select the appropriate technological solutions for Smart Spaces enabled by IoT and Big Data collection and analysis.
Making Judgements: Completing the course, the student will be able to judge the suitability, the capabilities, and the limitations of IoT based applications in the context of Smart Spaces. Further, the student will be able to identify issues, problems, or misleading results.
Communication Skills: On completion of the course, the student will be able to illustrate the theoretical and technical properties which characterize IoT based Smart Environments. The student will be able to interact and collaborate with peers and experts in the realization of a project or research.
Learning Skills: On completion of the course, the student will be able to autonomously extend the knowledge acquired during the study course by reading and understanding scientific and technical documentation.
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6
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ING-INF/05
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40
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-
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-
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-
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-
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Attività formative caratterizzanti
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ENG |
Gruppo opzionale:
SUPPLEMENTARY COURSES - (visualizza)
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12
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|
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9793955 -
CLOUD COMPUTING AND BIG DATA
(obiettivi)
Knowledge and understanding (Conoscenza e capacità di comprensione). Students will acquire a precise knowledge and understanding of fundamental concepts in the field of cloud computing, chiefly through a guided exploration of the main technological solutions available from the public Cloud, focusing on resources and services oriented to data storage, analysis, visualization and machine learning.
Applying knowledge and understanding (Capacità di applicare conoscenza e comprensione). Based on the operating knowledge acquired, students will develop an effective "toolset" of practical, application-oriented skills in leveraging the Cloud to cater for the typical needs of a data scientist: i.e. processing large datasets with a view to revealing meaningful patterns and relationships. Cloud implementations of state-of-the-art tools and frameworks like, e.g., MapReduce/Hadoop or TensorFlow, will be employed
Making judgements (Autonomia di giudizio). The student will develop the ability to choose the suitable Cloud-based resource for the Data Science scenario of interest, properly estimating the ensuing costs and performance gains, as well as consciously assessing the tradeoffs involved.
Communication skills (Abilità comunicative). The student will acquire the communication skills required to express and discuss, at a rigorous technical level, the benefits and (mostly cost-related) downsides of the Cloud for Data Science applications. In addition, the student will gain the ability, for presentation purposes, to effectively highlight the features of very large datasets by means of cloud-based visualization services.
Learning skills (Capacità di apprendimento). Students will become capable of profitably consulting technical documentation concerning Data Science-oriented Cloud services, in order to concretely put them to effective use
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6
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INF/01
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40
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-
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-
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-
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-
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Attività formative affini ed integrative
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ENG |
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9793943 -
BIG DATA SENSING, COMPRESSION AND COMMUNICATION
(obiettivi)
Data is growing and has grown very fast in the last years.”Big Data” analytics is challenging today because of the unprecedented large data volumes. In this course, we will describe the structure of data generated in big data sensing applications, by distinguishing the type and structure of data. Then we will discuss SoA methodologies which can be used to compress this data based on its intrinsic features; finally, communication protocols for remotely delivering this data will be described and detailed. In this way students will be provided with communication engineering competences allowing them to actively communicate with experts in various fields by providing focused and competent data analysis for every application, such as in scientific, technological or business fields. Students will also be able to exploit the competences gained for design processes of collection, compression and communication of heterogeneous big data.
This course will be of interest for students attending all paths for the following reasons:
For “Business and economics data scientists”, this course will allow to complement their business competences being able also to communicate with technical experts in the field.
For students in “Data driven applications for the IoT” and “Data for sciences”, this is a fundamental course to well understand the intrinsic nature of IoT big data.
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6
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ING-INF/03
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40
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-
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-
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-
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-
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Attività formative affini ed integrative
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ENG |
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9793930 -
MODELLING AND ANALYSIS FOR COMPLEX SYSTEMS
(obiettivi)
Knowledge and understanding. Students will learn the fundamental concepts of stationary processes and time series, how to estimate the features of a process, the main structures of prediction models, how to identify models starting from time series and how to validate models.
Applying knowledge and understanding. Students will be able to identify linear and non-linear models starting from time series by using popular software tools, such as MATLAB toolboxes, and validate their performances. Case studies will be proposed by using various kinds of dataset.
Making judgements. Students will be able to judge on the potential and limits of the model identification theory proposed in the course.
Communication skills. Students will be able to illustrate the basic aspects of model identification theory, interact and collaborate in teams with other experts.
Learning skills. Students will be able to autonomously extend their knowledge, drawing on the vast literature available in the field of time series model identification.
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6
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ING-INF/04
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40
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-
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-
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-
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-
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Attività formative affini ed integrative
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ENG |
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9793931 -
DATA AND METHODS FOR PUBLIC POLICIES EVALUATION
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6
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SECS-P/03
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40
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-
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-
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-
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-
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Attività formative affini ed integrative
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ENG |
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9793932 -
CREDIT RISK MANAGEMENT
(obiettivi)
Knowledge and understanding (Conoscenza e capacità di comprensione). Basic knowledge related to the recognition and management of financial risks from the core of the management processes of financial intermediaries.
Applying knowledge and understanding (Capacità di applicare conoscenza e comprensione). On completion, the student will be able to apply the measurement models of the main risks analyzed (credit risk, operational risk, interest rate risk on the banking book, liquidity risk)
Making judgements (Autonomia di giudizio). The ability to research, analyze and process public data and information also collected through scientific researches, with specific reference to the strategies up to the study of the problems concerning the assessment processes of the specific risks that banks incur in the activity of lending.
Communication skills (Abilità comunicative). On completion, the student will be able to communicate the results obtained, the problems encountered and the lessons learned, also based on independent judgment.
Learning skills (Capacità di apprendimento). On completion, the student will be able to individuate the components of credit risk, the organizational aspects of credit risk management and to choose the assessment tools for the diagnosis of credit risk.
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6
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SECS-P/11
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40
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-
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-
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-
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-
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Attività formative affini ed integrative
|
ENG |
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9793934 -
ANALYSIS OF QUESTIONNAIRE DATA
(obiettivi)
conoscenza e comprensione (Conoscenza e capacità di comprensione). Il corso fornirà i principali concetti e tecniche per la progettazione di questionari e l'analisi dei dati dei dati raccolti. Al termine, gli studenti acquisiranno conoscenze su: i) progettazione di un'indagine statistica; ii) tecniche per la progettazione del questionario; iii) metodi per l'analisi statistica dei dati raccolti e per la fornitura di report statistici.
Applicare conoscenza e comprensione (Capacità di applicare conoscenza e comprensione). Al termine, gli studenti saranno in grado di: i) progettare un'indagine statistica; ii) analizzare i dati raccolti attraverso metodi e modelli statistici adeguati; iii) fornire un report statistico di sintesi dei principali risultati.
Autonomia di giudizio. Al termine, gli studenti saranno in grado di scegliere un modello statistico adatto, applicare metodi statistici solidi ed eseguire le analisi utilizzando il software statistico R e/o SAS.
Abilità comunicative (Abilità comunicative). Al termine, gli studenti saranno in grado di presentare i risultati delle analisi statistiche attraverso opportuni report e quali conclusioni si possono trarre dalle analisi.
Capacità di apprendimento (Capacità di apprendimento). Al termine, gli studenti apprenderanno le principali tecniche statistiche per l'analisi dei dati del questionario e utilizzeranno software come R e/o SAS per effettuare analisi e modelli di dati.
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6
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SECS-S/01
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40
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-
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-
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-
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-
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Attività formative affini ed integrative
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ENG |
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9793937 -
DATA ANALYSIS FOR PUBLIC HEALTH
(obiettivi)
Il corso fornisce conoscenze specifiche sui metodi e tecniche per affrontare i principali temi di Sanità Pubblica. In particolare, al termine del corso, gli studenti dovranno possedere: i) buona conoscenza degli strumenti e dei metodi necessari alla formulazione di quesiti e obiettivi della propria ricerca; ii) conoscenza approfondita dei metodi statistici e degli strumenti informatici per l'elaborazione del piano di analisi statistica e per l'interpretazione dei risultati; iii) capacità di comunicazione utilizzando il linguaggio proprio della Sanità Pubblica e conoscenza del contesto biomedico. Queste abilità vengono acquisite attraverso lezioni attive e interattive, seminari, laboratori ed esercitazioni e attraverso lo studio del materiale didattico.
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6
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MED/42
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40
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-
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-
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-
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-
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Attività formative affini ed integrative
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ENG |
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9793936 -
DECISION SCIENCES
(obiettivi)
1. Conoscenza e capacità di comprensione (knowledge and understanding): Il percorso formativo del corso mira all'acquisizione dei principi teorici e delle principali metodologie applicative per il supporto alla decisione in ambito matematico-economico. La verifica dell'apprendimento è effettuata mediante esercizi da svolgere a casa e correggere in classe, nonché un esame finale, scritto e/o orale. Durante l'intero percorso formativo si effettua un controllo accurato e continuo della comprensione e dell'effettiva acquisizione da parte degli studenti delle conoscenze trasmesse, stimolandone una proficua ed attiva partecipazione.
2. Capacità di applicare conoscenza e comprensione (applying knowledge andunderstanding): La metodologia didattica è orientata anche all'acquisizione operativa ("saper fare") degli strumenti analitici e concettuali proposti durante l’insegnamento della disciplina, mirando allo sviluppo di una capacità critica dello studente nei confronti delle tematiche trattate, in un continuo processo di interazione di analisi-sintesi. Particolare attenzione è rivolta anche all’attività operativa dei futuri laureati, a volte chiamati ad affrontare nella professione problematiche similari a quelle oggetto del corso, spesso in differenti contesti, anche trasversali ed interdisciplinari.
3. Autonomia di giudizio (making judgements): Lo sviluppo di un'autonoma capacità critica nel contesto delle tematiche trattate è uno dei principali obiettivi formativi dell’insegnamento. Una buona acquisizione delle conoscenze teoriche e delle capacità operative previste nel programma dell’insegnamento non è sufficiente per una completa formazione dello studente, se tale preparazione non è accompagnata dall'acquisizione di un'approfondita, autonoma, socialmente e moralmente responsabile capacità di valutazione, di impostazione e di risoluzione di un problema, proponendo i metodi e le tecniche che si ritengono più adeguati all’analisi della problematica considerata, evidenziandone anche i limiti, spesso nascosti, delle metodologie adottate per modellare fenomeni reali. Invero, poiché uno degli obiettivi è quello di portare gli studenti sulla "frontiera della ricerca" in alcuni campi dell'economia matematica, si mirerà a sviluppare la capacità critica dello studente nella valutazione delle ipotesi poste alla base della modellizzazione.
4. Abilità comunicative (communication skills): Lo studente è messo in condizioni di relazionarsi e di trasferire a terzi, anche non specialisti, con chiarezza espositiva, precisione, padronanza di espressione e linguaggio tecnico appropriato, informazioni, analisi, giudizi di valore, progetti e proposte operative concernenti le decisioni economiche. In particolare, l’insegnamento dovrà mettere lo studente in grado di possedere e saper utilizzare gli strumenti idonei sia ad evidenziare gli aspetti quantitativi di tipici problemi relativi a tali decisioni, che a risolverli dopo la loro formalizzazione matematica.
5. Capacità di apprendimento (learning skills): Si forniscono agli studenti sin dall’inizio delle lezioni opportuni suggerimenti e stimoli per una partecipazione quanto più attiva possibile all'intero processo formativo e per un miglioramento del metodo di studio individuale, ai fini di un più efficace apprendimento della disciplina. Durante il corso delle lezioni si verificherà continuamente, argomento per argomento, se la trasmissione delle conoscenze avviene efficacemente, rivedendo eventualmente anche nel corso dell’anno il metodo di insegnamento, per meglio adeguarlo al raggiungimento concreto di questo importante obiettivo, tenendo anche conto della effettiva composizione dell’aula.
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6
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SECS-S/06
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40
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-
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-
|
-
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-
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Attività formative affini ed integrative
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ENG |
|
9793939 -
METHODOLOGY OF POLITICAL SCIENCE
(obiettivi)
1. Knowledge and understanding. By the end of the course, students will be able to identify theories, hypotheses, and methods used in empirical political science research. They will understand how big data and data science can contribute to the understanding of political and social problems and dynamics.
2. Applying knowledge and understanding. By the end of the course, students will apply different methods to political science research questions. They will be able to design and carry out a research project that uses innovative (big) data for understanding, describing, real-time monitoring and/or forecasting of political and social behaviour.
3. Making judgements. By the end of the course, students will analyze data to measure concepts, make comparisons, and draw inferences. They will be able to understand suitable and appropriate methodologies and designs for political and social science research.
4. Communication skills. By the end of the course, students will learn how to communicate political science concepts, theories, and methods in writing. They will also be able to present their research projects, findings and implications in front of an audience.
5. Learning skills. By the end of the course, students will learn how to recognise the most suitable method(s) for addressing research questions with the use of big data and data science methods.
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6
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SPS/04
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40
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-
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-
|
-
|
-
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Attività formative affini ed integrative
|
ENG |
|
9793970 -
PRIVATE LAW FOR INFORMATION TECHNOLOGY
(obiettivi)
Knowledge and understanding
The course of Private Law for Information Technology aims to analyze the impact of the Internet on legal rules and to identify the regulation of Internet behavior, with particular reference to the relationships between private subjects and to the complexity of the diffusion of artificial intelligence. The course aims also to give the keys to an adequate knowledge and understanding, as well as the normative sources and the relative interpretative principles, of the fundamental institutions of private law strictly connected to the Web in terms of subject regulation and protection of personal data, of the goods and of the circulation of internet rights, of the contract in general and of contracts on line.
2. Applying knowledge and understanding
At the end of the course, the student will be able to understand the legal issues raised by the technological context and to identify the solutions, both by reconstructing and interpreting the different situations and the legally relevant interests in the network on the private level, both by applying in practice the knowledge and tools acquired during the course of lessons and developed with a careful study of the subject.
3. Making judgements
The rapid development of information technology has exacerbated the need for robust personal data protection, the right to which is safeguarded by both European Union (EU) and Council of Europe (CoE) instruments. Safeguarding this important right entails new and significant challenges as technological advances expand the frontiers of areas such as surveillance, communication interception and data storage. This course is designed to familiarise students not specialised in data protection with this emerging area of the law. In particular, the student will be placed in a position to distinguish between positive and negative aspects, advantages and disadvantages associated with data protection regulation and the possible options between alternative forms of protection ready by the legislature. The teaching tends to let the student's ability to understand and explain key case law, summarising major rulings of both the Court of Justice of the European Union and the European Court of Human Rights.
4. Communication skills
The course must put the student in a position to transfer and apply the knowledge gained outside, using an exposure mode logical argument conforms to the main principles of matter and also suits a technically appropriate legal language. In particular, he must be able to provide opinions, advice and assistance on issues object of study.
5. Learning skills
Exceeding the matter must be based on a rigorous assessment in the examination of the achievement by the student of a level of preparation and competence that allows him to approach the study of the other teachings, also not legal, but which may present significant implications with them.
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6
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IUS/01
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40
|
-
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-
|
-
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-
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Attività formative affini ed integrative
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ENG |
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