Applied Computer Science and Artificial Intelligence

Educational objectives

General objectives:
The course aims at training professionals able to successfully face the challenges posed by the security problems of the information society.

Specific objectives:
The course includes the study of various models of access control, analysis of the main difficulties and resolutions of cryptographic problems and the main security protocols used in the network

Knowledge and understanding:
Upon passing the exam, the student will have knowledge and understanding of the bases of computer security and of the main technologies for the analysis and solution of security problems.

Apply knowledge and understanding:
The course enables students to apply their knowledge and understanding skills to solve IT security problems, with sufficient autonomy to deal with complex problems; and for the effective consultation of advanced scientific and technological documentation.

Autonomy of judgment:
The course aims to acquire autonomous interpretation skills to propose solutions to security problems congruent with the available technologies, and to continuously update the technological evolution, to formulate independent critical judgments contributing to the progress of system security.

Communication skills:
Students acquire the ability to present and to argue their ideas about the security problems faced and the solutions proposed, both with colleagues and with users

Next learning ability:
The course provides for the development of in-depth capabilities in the field of computer security both of methodological and technological aspects, to adapt to the progress of techniques and solutions to the most common security problems, and to continue autonomously to solve new problems. safety issues.

Educational objectives

General goals:
Familiarity with advanced machine learning techniques, both supervised and unsupervised; modeling skills of complex problems using deep learning techniques, and their application to diverse applicative settings.

Specific goals:
Topics include: deep neural networks, their training and the interpretation of results; convolutional networks and prominent architectures; theory of deep learning and convergence; programming frameworks for implementing advanced machine learning techniques; autoencoders; adversarial attacks.

Knowledge and understanding:
How neural networks work and their mathematical interpretation as universal approximators. Understanding the limits and potentials of advanced machine learning models.

Applying knowledge and understanding:
Design, implementation, deployment and analysis of deep learning architectures addressing complex problems in several applicative areas.

Critical and judgmental abilities:
To be able to evaluate the performance of different architectures, and to assess their generalization capabilities.

Communication skills:
To be able to communicate clearly how to formulate an advanced machine learning problem as well as its implementation, its applicability in realistic settings, and specific architectural and regularization choices.

Ability to learn:
Understanding alternative and more complex techniques such as generative models based on optimal transportation, scattering transforms and the energetic profile of neural networks. To be able to implement existing techniques efficiently, robustly and reliably.

Educational objectives

General objectives:

At the end of the course the students know the theories, models and rules that guide the project and the development and validation of usable interfaces and interactive systems.
Students who pass the exam are able to design interactive systems following the criteria of human-computer interaction, analyzing the user's role, the scenarios and the main tasks, and taking into account the implementation constraints through project cycles and development very short.

Specific objectives:

Knowledge and understanding:
At the end of the course the students know the theories, the models and the rules that guide the project of interfaces and usable interactive systems.They also know the principles of agile design centered on the user.

Apply knowledge and understanding:
Students apply the knowledge gained in designing an interface as a group work for the exam.

Critical and judgmental skills:
Students, also through practical exercises, acquire skills in the evaluation and validation of human computer interfaces and develop judgment on the usability of an interface and therefore on the effects of the use of the interface in terms of effectiveness, efficiency and satisfaction. .

Communication skills:
The students support two presentations of their group work during the two revisions scheduled with the teacher. The first review is carried out in the classroom and the presentation is therefore aimed at all colleagues in order to exercise communication skills.

Learning ability:
The learning capacity is stimulated through 1) guided and autonomous supervised planning activities; 2) exposure to realistic design problems by stimulating the independent search for non-standard solutions; 3) the presentation of real cases and stimulating their critical discussion.

Educational objectives

General goals:
Introduction to mathematical modelization of optimization problems, Linear and Integer programming and their applications in real contexts.

Specific goals:
To learn:
1. Main problem modelling techniques using mathematical and logical language
2. Main theory properties and their practical applications for optimization problems
3. Linear programming and simplex algorithm and its applications.
4. Competences for software for modelling and optimization

Knowledge and understanding:
develop
1. the ability of conciseness, of logical reasoning and problem solving trhough quantitative models;
2. the ability to describe and solve e risolvere (also at high level) computationally hard problems;
3. the ability to use english written bibliography and software;
4. the ability to identify precisely optimization problems and when they are linear integer or non-linear;
5. the ability to design a implementable version of mathematical optimization problem model and finding solution
for the model using appropriate algorithms. Interpreting the solutions.

Applying knowledge and understanding:
1. Real applications of optimization problems (especially on networks)
2. Skills on using software for modelling and optimization

Critical and judgmental skills:
Enabling autonomous thinking in the student by deepening the ability of mathematical reasoning of the student through the development of logical language and problem solving abilities.

Communication skills:
Group work aimed at solving optimization problems drawn from everyday cases, develop communication abilities in explaining and focusing optimization problems on concrete working examples

Learning ability:
Skills and theoretical tools acquired during the course are basic for more advanced courses on topics concerning computational complexity, network algorithms, graph theory.

Educational objectives

General goals:
The aim of the course is the study of java language support to server side programming, for the realization of web based applications. The course will also provide a critical comparative analysis of several approaches to realize the same functionalities, for a series of problems common in the development of web applications.

Specific goals:
Server Side programming through Java Servlet and JSP.

Knowledge and understanding:
Through this course, students will comprehend how the java language supports the realization of web applications. In particular, students will focus on the motivation at the basis of all the implementation choices with reference to the client server –architecture and network protocols in use.

Applying knowledge and understanding:
Through this course, students will develop the capability to determine among potential solutions which is the most suitable in terms of performance, security, portability and efficiency.

Critical and judgmental abilities:
The course will provide students with sufficient tools and methodologies to perform a comparative analysis of different potential solution methodologies.

Communication skills:
Students will be able to motivate the solutions adopted to design a specific web application, and to provide a comparative analysis of the chosen solutions with respect to other potential approaches.

Learning ability:
Students will develop the capability to autonomously study and search for new solutions and to evaluate new methodologies, technologies and models for the development of Web applications.

Educational objectives

General goals
The Business and Computer Science course analyses different types of information systems and how they can contribute to the success of a company's objectives. Also, it presents approaches and models to be used to assess the quality of ICT processes, software and services. Furthermore, it provides the basic knowledge to plan, manage and control IT projects.

Specific goals
• Knowledge and understanding
- Functional model and information structure of business processes
- integration and data control requirements of business information systems
- systems and technologies for developing and maintaining a successful e-business
- main areas of application of information systems in various market sectors
- IT organisation and IT quality assessment models
- basic background knowledge, techniques/methodologies and soft skills for ICT project management
- systems and technologies to develop&maintain a successful e-business
- main application areas of info systems in various industries
- ICT organisation and mainstream techniques (e.g. quality management)
- basic definitions (context), techniques/methodologies and soft skills for project management in ICT

• Application of knowledge and understanding
- Analyse different categories of requirements extracted from different categories of users (stakeholders) of information systems
- Select the appropriate model to assess the quality of ICT processes, software products and ICT services
- Develop a feasibility study by selecting the appropriate application and technology architecture
- Prepare, for a simple ICT project, a development plan respecting the constraints of time, cost, quality, and defining the appropriate organisation
- Monitor an ongoing ICT project, applying project management techniques
- Understand and evaluate lessons learnt in previous projects

• Critiquing and judgmental skills:
The combination of face-to-face theoretical lectures and practical exercises aimed at discussing and solving specific problems enables students to acquire the ability to assess the potential and limitations of approaches and models for the development of businesses and the achievement of their strategic objectives.

• Communication skills:
At the end of the course, students are able to illustrate and explain the main approaches to the management of the enterprise, its processes and ICT services to a variety of interlocutors who are heterogeneous in terms of background and professional role.

• Learning skills:
The student acquires the ability to independently conduct individual studies on specific topics related to information systems, process and service management. During the course, the student is stimulated to investigate topics of particular interest by consulting additional bibliographic material, such as academic articles, specialist books and websites. The acquisition of these skills is tested and assessed by analysing and solving new problems on the basis of the topics covered and the reference material distributed during the course.

Educational objectives

General Objectives:
The aim of the course is to deepen the main issues of legal regulation in information technologies, in companies and in the public administration, with reference to the topics of artificial intelligence, European regulation on the data processing and processing of personal data and electronic commerce and intellectual property relating to information technology. Legal instruments, protocols and standards of European cooperation in the use of artificial intelligence will also be presented. The course is structured in in-depth modules also with examination of practical cases.

Knowledge and understanding
At the end of the course the student is able to identify and develop the main legal knowledge in the field of data processing and artificial intelligence and therefore to operate effectively in public administrations. Furthermore, he is able to effectively participate in working groups on the use of artificial intelligence having clear the indispensable notions and legal responsibilities. The course allows the student to combine IT technological skills and economic and legal organizational skills regarding the use of IT/AI or IT/AI tools in the corporate and public sphere.

Ability to apply knowledge and understanding
For the realization of the training objectives, the teaching activities are divided into thematic in-depth modules, for the definition and intervention in specific contexts and to understand the needs of the operators.