The educational offer is organized in two curricula: "Computer Science and Technologies" and "ICT Innovation".

"Computer Science and Technologies" Curriculum 

Mandatory courses

Computability and computational complexity

Study of computability (what can be computed) and complexity (efficiency of computation). Complexity includes an abstract model for computation, and decision problems (halting problem). Computability studies the various time and space complexity classes, reductions between classes and the fundamental theorems (such as Cook, Savitch etc).
6 credits

Innovation and Entrepreneurship Basic

The goal of the course is to provide students with some fundamentals in the field of innovation theory and entrepreneurial practice, also focusing on the development of “soft skills” such as presentation, team working, critical thinking and creativity. The course matches these core notions to in-class debates, carried out through case studies in the form of “Technology Battles”.
6 credits
12 credits from the following courses:

Concurrency

The goal of the class is to obtain a good understanding of concurrency and of multithreading at work in shared memory models.
6 credis

Machine learning

Provide knowledge of both theoretical and practical aspects of machine learning. Present the main techniques of machine learning and probabilistic reasoning.
6 credits

Simulation and performance evaluation

Introduction to modeling techniques. Stochastic processes, memory, correlation and Markov processes. Event-driven simulation. Data analysis and measure confidence estimation.
6 credits
6 credits from the following courses:

Computer Vision and Multimedia Analysis

The course will be will be offered in A.Y. 2017/18
6 credits

Advanced remote sensing systems

The course will be will be offered in A.Y. 2017/18
6 credits

Advanced computing architectures

The objective of this course is to provide the students the required concepts for the understanding, the design and the evaluation of advanced processing architectures, with emphasis on the various forms of parallelism. At the end of the course, the student will be able to comprehend the organization of recent central processing units, and to design customized architectures, analyzing and evaluating the effects of architectural choices, identifying the critical components, and comparing different solutions in terms of performance and cost, to select the optimal ones in various domains of application.
6 credits

Network modeling and design

The goal of the course is to provide advanced know-how on modeling and design of tlc networks. The student will learn analytical methodologies for designing communication networks and will be able to apply those to current and future networks; he/she will learn the behaviour of Internet transport protocols and will be able to design modifications or new protocols.
6 credits

Multimedia Data Security

Nowadays great facility to access information implies the need to study data protection techniques. The objective of the course is the investigation of some methodologies which guarantee secure access to multimedia data, through various data hiding and digital forensics techniques. After an introduction to Digital Rights Management concepts and models for multimedia content protection, the course is specifically devoted to digital watermarking and digital forensics. A general overview of these concepts introduces the description and evaluation of specific techniques for multimedia data.
6 credits

Choose one among the following areas and select 18 cfu from it. Then select additional 18 cfu among the courses listed in the other area/s.

DATA SCIENCE AREA

Intelligent Optimization for data science

To give a first theoretical introduction, supported by concrete examples, to the topic of using automation (and mathematical optimization) for solving problems and delivering improved solutions. The course is suggested as a second phase, preceded by the course “Machine learning for data science”. "Data Scientist" has become a popular occupation, dealing with starting from rich and abundant data sources, building mathematical models using the data, presenting and communicating the obtained insights, delivering improving solutions. Creative disruption and innovation in industry and services are the final goals.
6 credits

Laboratory of Business Process Management and Integration

The course focuses on principles, architectures and tools for modeling, executing, and managing business processes. It covers several types of processes, including document-oriented processes typical of office automation, enterprise integration processes (business processes that integrate enterprise applications and therefore automate enterprise processes) and Web processes (processes that integrate Web services and in general Web content, as done by service composition tools and by mashups). In addition, the course will look at process monitoring and management technologies, and at deployment technologies with particular emphasis on cloud computing and at deploying processes and services on the cloud.
6 credits

Spatial Databases

Study of Spatial databases, with application to GIS.
6 credits

Data Mining

This is an introductory course to data mining and massive data analytics. In this course we will talk about some basic data mining techniques, such as association rules, sequential patterns, clustering, and classification. We will discuss different flavors of these techniques, and comment on their strong and weak points. Finally, we will also talk about the new trends in data analysis, and explore some emerging applications in this area, such as mining of streaming data (that is, data that is continuously generated).
6 credits

Big Data and Social Networks

Data management has entered the era of Big Data. The aim of the course if to prepare the future data scientists by providing them with all the required background for using the modern technologies to store, process and analyse the huge volumes of the various forms of data that we are producing daily. Special focus is made on data produced by social media and various techniques for analysing them are presented.
6 credits

Laboratory of Biological Data Mining

Goal of the course is to give the notions of data analysis and statistics that are necessary in order to support or doing genomic and transcriptomic data analysis.
6 credits

Language Understanding Systems

Language technology is the fundamental component of artificial intelligence systems based on natural language. This technology supports the analysis of very large and diverse conversations (e.g. web docs, blogs, emails, telephone..) and the generation of summaries/reports etc.. Language understanding systems supports the design of  human-machine dialogue systems  oriented at resolving user problems of different complexity. The lectures and lab sessions will include, a) basic concepts and models for language  understanding, b) rule-based and statistical models of language understanding as well as c) theories and models of human conversations. Case studies in the web and mobile telephone application domains, social media ( e.g. social robots ) amongst others, will be presented.
6 credits

Knowledge representation in an open world

The goal of this course is to provide motivations, definitions and techinques in support of the usefulness of logic in the effective and efficient modeling of data and knowledge. The course will have succeeded if it stimulates the interested students to continue their career with higher interest into logic-based models for data and knowledge representation in their own field of expertise, and to produce computer-processable solutions of relevant problems.
6 credits

High Throughput Sequencing Data Analysis

Latest technological advances provide the scientific community with unprecedented opportunity to study human genomics that is highly informative in the context of diseases. Computational approaches are key to interpret genomics data. The formative aims of the course in computational human genomics are:
- to provide an understanding of the main challenges in terms of genomics data analyses;
- to provide analytical skills for the use of bioinformatics and computational biology tolls currently used in genomics, transcriptomics and epigenetics studies.
At the end of this course the students should be able to:
1. describe the advantages of next generation sequencing techniques;
2. describe how human genomics experiments are relevant to precision medicine;
3. explain and comment on the main computational challenges of next generation sequencing data analyses;
4. discern best computational option(s) to address a specific question related to human genomics;
5. utilize tools to mine genomics data;
6. understand main concepts and approaches presented in high level journal papers.
6 credits

Advanced Natural Language Processing and Information Retrieval

Il corso mira a fornire le nozioni essenziali e avanzate di due discipline importanti della moderna Informatica: l’elaborazione automatica del linguaggio naturale, Natural Language Processing (NLP), e il recupero automatico di informazione, Information Retrieval (IR).
6 credits

Affective computing

This class explores computing research that relates to, arises from, or deliberately influences emotion. The aim is to identify the important research issues, and to ascertain potentially fruitful future research directions in relation to the multimodal emotion analysis and to human-computer interaction. At the end of the course the students will know the state of the art in affective computing and will be able to write a research proposal on this theme.
6 credits

SERVICE DESIGN AND ENGINEERING AREA 

Introduction to Service Design and Engineering

The course focuses on current methodologies, languages and tools to support the "service-oriented" approach to programming and business process management, based on the idea of composing applications by discovering and invoking network-available services rather than building new applications to accomplish some task. In this approach, services are self-contained processes - deployed over standard middleware platforms, e.g., J2EE - that can be described, published, located, and invoked over a network. In this course students will have the opportunity to be introduced to this new approach, to study state-of-the-art methodologies, languages and tools and to develop appropriate skills by working at first on individual activities and subsequently on individual or group projects to be carried out during both the supervised and unsupervised laboratory activities.
6 credits

Laboratory of Service Design and Engineering

The course will be will be offered in A.Y. 2017/18.
6 credits

Organizational Information Systems

The goals of the course are: 1. Learn basic concepts about modelling business organizations and business processes;
2. Learn information system technologies and architectures used to support the operation of organizations;
3. Understand how to manage organization information systems and to ensure Information Assurance;
4. Introduce new trends in organizational information systems.
6 credits

Requirements Engineering

The goals of the course are: 
1. Learn concepts, techniques, and tool for acquiring, analyzing, and eliciting requirements for a software system;
2. Develop an understanding for the engineering issues that form the background to the requirements engineering process and an awareness of some pitfalls in this process;
3. Learn to evaluate different tools and techniques, also to conduct a requirements definition project;
4. Learn to manage requirements of software systems.
Introduce some emergent issues in requirement engineering.
6 credits

Cyber Security Risk Assessment

The objective of the course is to learn how to assess the risks in a real life problem from high-level controls down to security architecture.
6 credits

Security Testing

This course aims at providing the foundations behind security testing, including attack models and taxonomy, static analysis for vulnerability detection and test case generation. The laboratory will be focused on the course project, which will give the students a hands-on opportunity to see the analysis and testing techniques applied to a real case study.
6 credits

Agent-Oriented Software Engineering

The objective of the course is to examine and explore the credentials of agent-based approaches as a software engineering paradigm, and to gain an insight into what agent-oriented software engineering will look like. We also explore how to develop multiagent systems using JADE.

6 credits

Formal methods

Formal methods are increasingly used as powerful specification, verification and early debugging methods in the development of industrial SW and HW systems. This course provides an introduction to Formal Techniques and Tools for the specification and verification of Hardware and Software platforms. Apart from an introduction on formal techniques and their benefits, the course will concentrate mainly on formal verification and techniques and, in particular, on Model Checking (MC). A laboratory will be given in which the students will experience MC techniques by means of the MC NuSMV and SPIN.
12 credits

SYSTEMS AND NETWORKS AREA

Distributed systems 1

The goal of the course is to expose the students to the core principles and technologies of distributed systems. The biggest portion of the course is dedicated to the fundamental concepts in distributed systems, such as naming, synchronization, fault tolerance, replication and consistency, taught through the study of classical
algorithms. The goal of the latter is either to illustrate commonly-used solutions, or to highlight fundamental principles and techniques concerned with the problem at hand. A second portion of the course is devoted to technologies commonly used to develop distributed applications. Alongside to standard lectures, this topic includes hands-on sessions in the lab, focused on the development of simple applications. 
Finally, the course includes a few lectures on advanced "hot topics" in distributed systems, such as the back-end of large-scale distributed systems (e.g., Google, Amazon, Yahoo), wireless sensor networks, peer-to-peer systems
6 credits

Distributed Systems 2

The goal of this course is to provide students with advanced notions on the main problem and techniques in the designe and implementation of distributed systems. The course is a follow-up of "Distributed Systems 1".
6 credits

Wireless Mesh and Vehicular Networks

The course goal is understanding and learning to analyse, design and deploy wireless networks, and services upon them, based on short range communication devices, normally (but not always) based on 802.11 PHY and MAC standards (not necessarily the usual plug-and-play WiFi we are all familiar with).
Teaching spans from the physical to the application layer, taking a holistic, cross-layer design approach to learn how to build networks that work correctly and efficiently support the applications they are meant for.
Applications include Community Networks as liberation technologies to design alternative Internets over Wireless Mesh Networks WMN) and Safety as well as Cooperative Driving systems based on direct communication between vehicles and with the infrastructure (V2X Vehicular Networks).
6 credits

Laboratory of Wireless Sensor Networks

Wireless sensor networks (WSNs) are networked embedded systems composed of tiny devices equipped with computation, communication, and sensing/actuating capabilities. These networks recently attracted great interest in a number of application domains concerned with monitoring and control of physical phenomena, as they enable dense and untethered deployments at low cost and with unprecedented flexibility.
The course aims at providing students with an introduction to this exciting field. On one hand, classroom lectures will analyze and concisely present the salient aspects of WSNs, by covering all the topics from the physical hardware, sensing, and communication, through the networking protocols and software layers, up to application issues. Lectures will make frequent reference to real-world deployments, some of which are in Trento and nearby locations. On the other hand, laboratory sessions will be the opportunity for students to experiment "hands-on" the peculiarity of this technology by developing small projects and testing deployment issues, with an emphasis on the development environment provided by TinyOS 2.0.
6 credits

Web Architectures

At the end of the course the student will be familiar with the main issues related to web architectures and with several web technologies. It is necessary to be familiar with object oriented programming and Java A basic knowledge of computer networks (TCP/IP stack, sockets) and of Databases and SQL language is required.
6 credits

Network Security

This course focuses on technological and infrastructural security aspects of computer networks. In this course we are interested in both defensive and attacking aspects of network security.
6 credits

Laboratory of Applied robotics

In this course the student will be introduced to a complete methodology for embedded control systems design. After an introduction to the mathematical foundations of classical linear control design, he/she will start working on a project work to carry out all the necessary phases to come up with a complete implementation of the embedded controller.
6 credits

Real-Time Operating Systems and Middleware

The Real-Time Operating Systems and Middleware course will introduce the concept of real-time application, and teach the student how to design, develop, and implement a real-time system. In particular, the requirements on the operating system kernel will be explained. The course will consider different kinds of Real-Time systems, for supporting applications ranging from multimedia (soft real-time) to control and automation.
6 credits
Free choice courses - select 24 free choice credits*

Science Technology and Business

This course is proposed to students of the specialist degree. The aim of the course is to improve knowledge on scientific methods for the companies. In particular, some basic concepts on organizational operations, decisional processes and strategic choices will be introduces in order to deeply analyze how companies improve their business models. Some scientific instruments (IT and ICT applications, KM theories and methods) will be presented to understand how organizations can efficiently and effectively improve their business. Some concrete cases will be used during the teaching classes.
6 credits

Privacy and Intellectual Property Rights

The aim of the course is to introduce the students to the basic principles of Privacy and Intellectual Property.
6 credits

Introduction to Computer and Network Security

 
6 credits

Participatory Design

The course aims at providing a theoretical framework and empirical experience of Participatory Design, including planning a PD project, running it, communicating the results.
6 credits

User-centered design

User-centered design aims to provide students with an understanding of concepts and techniques for designing usable and engaging interactive systems. A major emphasis will be devoted to practical aspects of user-centred design, including requirements elicitation, prototyping and evaluation.
6 credits

Statistics of Stochastic Processes

To give a basic knowledge on the problems concerning the statistical analysis of data from time series; especially, to develop good competences in the structure of linear ARMA models, often used in the analysis of economic data, and of the relative methods of analysis.
6 credits

Inverse problems and optimization

The course will review the fundamentals and the main issues of inverse problems then focusing on classical/state‐of‐the‐art and recently introduced inverse solution procedures and algorithms. Applicative examples including software exercises will corroborate the theoretical concepts.
9 credits

Business in ICT

The goals of the course are the following:
1. Stimulating paricipants business orientation
2. Nurturing a series of entrepreneurial attitudes
3. Giving participants a tool kit and the opportunity to test it in practice
9 credits

Statistical Models

The student, at the end of this class, will be able to use linear and generalized linear models to study the relation between continuous or discrete variables and predictors. She/He will learn fundamental aspects of the theory and the way to apply them to practical case trough the use of a statistical software.
6 credits

Cryptography

The students will understand the basics of cryptography and correctly implement the main algorithms.
6 credits

Formal Techniques for Cryptographic Protocol Analysis

The aim of the course is to introduce students to the formal techniques for the automatic verification of security properties on cryptographic protocols. After discussing the theoretical foundations of programming languages, the course applies the related techniques to model protocols and construct algorithms which verify their robustness to attacks.
6 credits

Introduction to Cell Biology

The course provides essential information about structural and functional organization of the cell, in the context of living organisms, necessary for placing bioinformatic data in a biological context.
9 credits

Technical Writing 

The course aims to extend students’ knowledge of grammatical, lexical and textual features of written academic English in a scientific context from B1 to B2 level, and to develop students’ fluency in speaking English. An active approach is used, with students producing written texts and then correcting them individually and as a group.
6 credits

Project course

To carry out a project work under the supervision of a professor of the Department.
 6 credits

Research project

The course objective is to develop autonomous research capabilities by reading existing literature, building state-of-the-art knowledge, and identifying personal innovative research directions. The course could help in choosing a thesis topic and in beginning the thesis work. Each student will be assigned a project work and an academic tutor.
12 credits

Bayesian Statistics

The purpose of the course is to address the study of the foundations of Bayesian statistics starting from the basic principles of the probability calculus. The course is divided into two modules: the first one will be devoted to estimation and to hypothesis testing based on the Bayesian approach to inference and intends to highlight the similarities and differences with the classical Fisher’s approach. Particular attention will be paid to the study of some common concepts to the two inferential approaches (for example, sufficiency, likelihood, independence/exchangeability) by stressing the different interpretations and their main consequences in terms of inferential results. The students during the course will have the opportunity to familiarize themselves with the principal theorems, logical developments, ideas and issues that underlie the different statistical techniques covered and learn to recognize them as natural extensions and consequences of the concepts introduced previously in the courses of probability and mathematical statistics.
6 credits

ICT Innovation - Product Design and Development

Present the key steps of the design and development of a product and guide the students (grouped into teams) into the development of a "product" and not just a "project".
6 credits

Offensive Technologies

Scientific progress in computer security is driven by a mutual understandings of attack and of defense. The course aims at advancing the concrete student's knowledge of attacks on operating systems, networks, and applications, and their societal implications.

12 credits

*Select 24 free-choice credits among the courses offered by the University of Trento. The courses above listed and the courses suggested in the ESSE3 online tool for study plan are automatically approved. In all other cases, a personalized study plan must be completed and submitted to the commission for study plan examination.

Mandatory courses

Thesis

The final exam in a Master’s degree course consists in discussing an original dissertation, in Italian or in English, submitted as a written document, on a subject proposed by the student. The dissertation shall be written under the supervision of one or more lecturers, of which one must be chosen among the faculty of the Department or among the professors involved in the programme.
24 credits

Internship

The internship is a period of “working training” in a professional/productive body/company in line with the study plan of students, which allow them to test and enhance their knowledge: it is an important element of the professional training and the specialization contents, as well as a support to future professional choices. 
6 credits

 "ICT Innovation" Curriculum

Specialization area: Service design and Engineering (SDE) (Entry point)

Mandatory courses

Business Development Laboratory

The goal of the class is to provide some basic tools, skills and knowledge on the development and presentation of a de-hydrated business plan according to the following principles:
- starting with the ideation and identification of a business concept (service or product), including those focused on business and/social innovation, up to the identification of other aspects such as the target market, the business model, the supply chain, the risk management plan and the exit strategy, and basic financial assumptions
- assuming that the intrinsic technological value of the identified concept is not the only core element for the success of the business plan but that other factors, such as the competitive arena or the users’ acceptance are as well fundamental. Upon completion of the course students will be able to deliver besides the business plan, a presentation of their concept before an audience/ jury as well as a pitch also relying on the use of multimedia tools. Those who are interested can participate in the IBC (Intel Business Challenge) competing with other teams at the European/ Worldwide level.
9 credits

Innovation and Entrepreneurship Basic

The goal of the course is to provide students with some fundamentals in the field of innovation theory and entrepreneurial practice, also focusing on the development of “soft skills” such as presentation, team working, critical thinking and creativity. The course matches these core notions to in-class debates, carried out through case studies in the form of “Technology Battles”.
6 credits

ICT Innovation

Present the key steps of the design and development of a product and guide the students (grouped into teams) into the development of a "product" and not just a "project".
9 credits

Introduction to Service Design and Engineering

The course focuses on current methodologies, languages and tools to support the "service-oriented" approach to programming and business process management, based on the idea of composing applications by discovering and invoking network-available services rather than building new applications to accomplish some task. In this approach, services are self-contained processes - deployed over standard middleware platforms, e.g., J2EE - that can be described, published, located, and invoked over a network. In this course students will have the opportunity to be introduced to this new approach, to study state-of-the-art methodologies, languages and tools and to develop appropriate skills by working at first on individual activities and subsequently on individual or group projects to be carried out during both the supervised and unsupervised laboratory activities.
6 credits

Big Data and Social Networks

Data management has entered the era of Big Data. The aim of the course if to prepare the future data scientists by providing them with all the required background for using the modern technologies to store, process and analyse the huge volumes of the various forms of data that we are producing daily. Special focus is made on data produced by social media and various techniques for analysing them are presented.
6 credits

Laboratory of Business Process Management and Integration

The course focuses on principles, architectures and tools for modeling, executing, and managing business processes. It covers several types of processes, including document-oriented processes typical of office automation, enterprise integration processes (business processes that integrate enterprise applications and therefore automate enterprise processes) and Web processes (processes that integrate Web services and in general Web content, as done by service composition tools and by mashups). In addition, the course will look at process monitoring and management technologies, and at deployment technologies with particular emphasis on cloud computing and at deploying processes and services on the cloud.
6 credits

Web architectures

At the end of the course the student will be familiar with the main issues related to web architectures and with several web technologies. It is necessary to be familiar with object oriented programming and Java A basic knowledge of computer networks (TCP/IP stack, sockets) and of Databases and SQL language is required.
6 credits
18 credits from the following courses:
Introduction to Computer and Network Security
 
6 credits

Distributed systems 1

The goal of the course is to expose the students to the core principles and technologies of distributed systems. The biggest portion of the course is dedicated to the fundamental concepts in distributed systems, such as naming, synchronization, fault tolerance, replication and consistency, taught through the study of classical algorithms. The goal of the latter is either to illustrate commonly-used solutions, or to highlight fundamental principles and techniques concerned with the problem at hand. A second portion of the course is devoted to technologies commonly used to develop distributed applications. Alongside to standard lectures, this topic includes hands-on sessions in the lab, focused on the development of simple applications. Finally, the course includes a few lectures on advanced "hot topics" in distributed systems, such as the back-end of large-scale distributed systems (e.g., Google, Amazon, Yahoo), wireless sensor networks, peer-to-peer systems.
6 credits

Machine learning

Provide knowledge of both theoretical and practical aspects of machine learning. Present the main techniques of machine learning and probabilistic reasoning.
6 credits

Organizational Information Systems

The goals of the course are: 
1. Learn basic concepts about modelling business organizations and business processes;
2. Learn information system technologies and architectures used to support the operation of organizations;
3. Understand how to manage organization information systems and to ensure Information Assurance;
4. Introduce new trends in organizational information systems.
6 credits

Requirements Engineering

The goals of the course are: 
1. Learn concepts, techniques, and tool for acquiring, analyzing, and eliciting requirements for a software system;
2. Develop an understanding for the engineering issues that form the background to the requirements engineering process and an awareness of some pitfalls in this process;
3. Learn to evaluate different tools and techniques, also to conduct a requirements definition project;
4. Learn to manage requirements of software systems.
Introduce some emergent issues in requirement engineering.
6 credits

Participatory Design

The course aims at providing a theoretical framework and empirical experience of Participatory Design, including planning a PD project, running it, communicating the results.
6 credits

Agent-Oriented Software Engineering

The objective of the course is to examine and explore the credentials of agent-based approaches as a software engineering paradigm, and to gain an insight into what agent-oriented software engineering will look like. We also explore how to develop multiagent systems using JADE.

6 credits

Cyber Security Risk Assessment

The objective of the course is to learn how to assess the risks in a real life problem from high-level controls down to security architecture.
6 credits

Privacy and Intellectual Property Rights

The aim of the course is to introduce the students to the basic principles of Privacy and Intellectual Property.
6 credits

Intelligent Optimization for data science

To give a first theoretical introduction, supported by concrete examples, to the topic of using automation (and mathematical optimization) for solving problems and delivering improved solutions. The course is suggested as a second phase, preceded by the course “Machine learning for data science”. "Data Scientist" has become a popular occupation, dealing with starting from rich and abundant data sources, building mathematical models using the data, presenting and communicating the obtained insights, delivering improving solutions. Creative disruption and innovation in industry and services are the final goals. 
6 credits

Specialization area: Service design and Engineering (SDE) (Exit point)

Mandatory courses

Innovation and Entrepreneurship Studies in ICT

An introductory course on Innovation, Entrepreneurship and Epistemology of Science
6 credits

Thesis

The final exam in a Master’s degree course consists in discussing an original dissertation, in Italian or in English, submitted as a written document, on a subject proposed by the student. The dissertation shall be written under the supervision of one or more lecturers, of which one must be chosen among the faculty of the Department or among the professors involved in the programme.
24 credits

Internship

The internship is a period of “working training” in a professional/productive body/company in line with the study plan of students, which allow them to test and enhance their knowledge: it is an important element of the professional training and the specialization contents, as well as a support to future professional choices. 
6 credits
Free-choice courses for a maximum of 24 credits

Introduction to Computer and Network Security

 
6 credits

Big Data and Social Networks

Data management has entered the era of Big Data. The aim of the course if to prepare the future data scientists by providing them with all the required background for using the modern technologies to store, process and analyse the huge volumes of the various forms of data that we are producing daily. Special focus is made on data produced by social media and various techniques for analysing them are presented.
6 credits

Privacy and Intellectual Property Rights

The aim of the course is to introduce the students to the basic principles of Privacy and Intellectual Property
6 credits

Human-computer interaction

This course aims to provide students with an understanding of concepts and techniques for designing usable and engaging interactive systems. The course will complement an in depth review of usability engineering with basic knowledge of cognitive processes necessary to operate interactive systems and of the social impact of technology. A major emphasis will be devoted to practical aspects of user-centred design, including requirements elicitation, prototyping and evaluation.
6 credits

Machine learning

Provide knowledge of both theoretical and practical aspects of machine learning. Present the main techniques of machine learning and probabilistic reasoning.
6 credits

Organizational Information Systems

The goals of the course are: 
1. Learn basic concepts about modelling business organizations and business processes;
2. Learn information system technologies and architectures used to support the operation of organizations;
3. Understand how to manage organization information systems and to ensure Information Assurance;
4. Introduce new trends in organizational information systems.
6 credits

Requirements Engineering

The goals of the course are: 
1. Learn concepts, techniques, and tool for acquiring, analyzing, and eliciting requirements for a software system;
2. Develop an understanding for the engineering issues that form the background to the requirements engineering process and an awareness of some pitfalls in this process;
3. Learn to evaluate different tools and techniques, also to conduct a requirements definition project;
4. Learn to manage requirements of software systems.
Introduce some emergent issues in requirement engineering.
6 credits

Privacy and Intellectual Property Rights

The aim of the course is to introduce the students to the basic principles of Privacy and Intellectual Property.
6 credits

Data Mining

This is an introductory course to data mining and massive data analytics. In this course we will talk about some basic data mining techniques, such as association rules, sequential patterns, clustering, and classification. We will discuss different flavors of these techniques, and comment on their strong and weak points. Finally, we will also talk about the new trends in data analysis, and explore some emerging applications in this area, such as mining of streaming data (that is, data that is continuously generated).
6 credits

Specialization area: Security & Privacy (S&P) (Entry point)

Mandatory courses

Business Development Laboratory

The goal of the class is to provide some basic tools, skills and knowledge on the development and presentation of a de-hydrated business plan according to the following principles:
- starting with the ideation and identification of a business concept (service or product), including those focused on business and/social innovation, up to the identification of other aspects such as the target market, the business model, the supply chain, the risk management plan and the exit strategy, and basic financial assumptions
- assuming that the intrinsic technological value of the identified concept is not the only core element for the success of the business plan but that other factors, such as the competitive arena or the users’ acceptance are as well fundamental.
Upon completion of the course students will be able to deliver besides the business plan, a presentation of their concept before an audience/ jury as well as a pitch also relying on the use of multimedia tools. Those who are interested can participate in the IBC (Intel Business Challenge) competing with other teams at the European/ Worldwide level.
9 credits

Innovation and Entrepreneurship Basic

The goal of the course is to provide students with some fundamentals in the field of innovation theory and entrepreneurial practice, also focusing on the development of “soft skills” such as presentation, team working, critical thinking and creativity. The course matches these core notions to in-class debates, carried out through case studies in the form of “Technology Battles”.
6 credits

ICT Innovation

Present the key steps of the design and development of a product and guide the students (grouped into teams) into the development of a "product" and not just a "project".
9 credits

Cyber Security Risk Assessment

The objective of the course is to learn how to assess the risks in a real life problem from high-level controls down to security architecture.
6 credits

Network Security

This course focuses on technological and infrastructural security aspects of computer networks. In this course we are interested in both defensive and attacking aspects of network security.
6 credits

Security Testing

This course aims at providing the foundations behind security testing, including attack models and taxonomy, static analysis for vulnerability detection and test case generation. The laboratory will be focused on the course project, which will give the students a hands-on opportunity to see the analysis and testing techniques applied to a real case study.
6 credits

Cryptography

The students will understand the basics of cryptography and correctly implement the main algorithms.
6 credits

Privacy and Intellectual Property Rights

The aim of the course is to introduce the students to the basic principles of Privacy and Intellectual Property.
6 credits

Free-choice courses for a maximum of 12 credits

Machine learning

Provide knowledge of both theoretical and practical aspects of machine learning. Present the main techniques of machine learning and probabilistic reasoning.
6 credits

Offensive Technologies

Scientific progress in computer security is driven by a mutual understandings of attack and of defense. The course aims at advancing the concrete student's knowledge of attacks on operating systems, networks, and applications, and their societal implications.
12  credits

Multimedia Data Security

Nowadays great facility to access information implies the need to study data protection techniques. The objective of the course is the investigation of some methodologies which guarantee secure access to multimedia data, through various data hiding and digital forensics techniques. After an introduction to Digital Rights Management concepts and models for multimedia content protection, the course is specifically devoted to digital watermarking and digital forensics. A general overview of these concepts introduces the description and evaluation of specific techniques for multimedia data.
6 credits

Formal Techniques for Cryptographic Protocol Analysis

The aim of the course is to introduce students to the formal techniques for the automatic verification of security properties on cryptographic protocols. After discussing the theoretical foundations of programming languages, the course applies the related techniques to model protocols and construct algorithms which verify their robustness to attacks.
6 credits

Distributed systems 2

The goal of this course is to provide students with advanced notions on the main problem and techniques in the designe and implementation of distributed systems. The course is a follow-up of "Distributed Systems 1".
6 credits

Organizational Information Systems

The goals of the course are: 1. Learn basic concepts about modelling business organizations and business processes; 2. Learn information system technologies and architectures used to support the operation of organizations; 3. Understand how to manage organization information systems and to ensure Information Assurance; 4. Introduce new trends in organizational information systems
6 credits

Introduction to Computer and Network Security

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6 credits

Specialization area: Security & Privacy (S&P) (Exit point)

Mandatory courses

Innovation and Entrepreneurship Studies in ICT

An introductory course on Innovation, Entrepreneurship and Epistemology of Science.
6 credits

Thesis

The final exam in a Master’s degree course consists in discussing an original dissertation, in Italian or in English, submitted as a written document, on a subject proposed by the student. The dissertation shall be written under the supervision of one or more lecturers, of which one must be chosen among the faculty of the Department or among the professors involved in the programme.
24 credits

Internship

The internship is a period of “working training” in a professional/productive body/company in line with the study plan of students, which allow them to test and enhance their knowledge: it is an important element of the professional training and the specialization contents, as well as a support to future professional choices. 
6 credits
Free-choice courses for a maximum of 24 credits

Offensive Technologies

Scientific progress in computer security is driven by a mutual understandings of attack and of defense. The course aims at advancing the concrete student's knowledge of attacks on operating systems, networks, and applications, and their societal implications.
12 credits

Multimedia Data Security

Nowadays great facility to access information implies the need to study data protection techniques. The objective of the course is the investigation of some methodologies which guarantee secure access to multimedia data, through various data hiding and digital forensics techniques. After an introduction to Digital Rights Management concepts and models for multimedia content protection, the course is specifically devoted to digital watermarking and digital forensics. A general overview of these concepts introduces the description and evaluation of specific techniques for multimedia data.
6 credits

Project course

To carry out a project work under the supervision of a professor of the Department.
6 credits

Privacy and Intellectual Property Rights

The aim of the course is to introduce the students to the basic principles of Privacy and Intellectual Property.
6 credits

Research project

The course objective is to develop autonomous research capabilities by reading existing literature, building state-of-the-art knowledge, and identifying personal innovative research directions. The course could help in choosing a thesis topic and in beginning the thesis work. Each student will be assigned a project work and an academic tutor.
6 credits

Security Testing

This course aims at providing the foundations behind security testing, including attack models and taxonomy, static analysis for vulnerability detection and test case generation. The laboratory will be focused on the course project, which will give the students a hands-on opportunity to see the analysis and testing techniques applied to a real case study.
6 credits

Organizational Information Systems

The goals of the course are: 1. Learn basic concepts about modelling business organizations and business processes; 2. Learn information system technologies and architectures used to support the operation of organizations; 3. Understand how to manage organization information systems and to ensure Information Assurance; 4. Introduce new trends in organizational information systems.
 credits

Distributed systems 2

The goal of this course is to provide students with advanced notions on the main problem and techniques in the designe and implementation of distributed systems. The course is a follow-up of "Distributed Systems 1".
6 credits
Aggiornato il
10 April 2018