Computer Science

Educational objectives

General objectives:
Introduction to programming through the Python language.

Specific objectives:
Introduction to programming through the Python language.
Data types, variables, assignments, control structures, functions, classes, modules and Input/Output.
Data structures: arrays, strings, lists, tuples and dictionaries.
Design and development of programs through procedural programming and object-oriented programming.
Recursive and iterative algorithms.
Python libraries for graphics, file handling, text/html processing and internet access.
Program debugging and testing.

Knowledge and understanding:
Understand and define a problem's requirements.
Choose how to represent the input and what data structures to use for intermediate computations and output.
Define the algorithm solving the problem.
Code the algorithm as a Python program.
Modularize the program as small separate functions/methods.
Test that the program satisfies the requirements.

Apply knowledge and understanding:
The student will work at home on a series of programming tasks, through the whole course, to practice and to show what has been learned.
At the end of the course, the exam will be based on a lab test where she should solve and program various programming exercises.

Critical and judgmental skills:
The student, at the end of the course, should be able to autonomously choose how to solve a programming task (analysis, implementation and test).

Communication skills:
It is very important that the student has good text comprehension abilities for the problem analysis and requirement definition phase.

Learning ability:
The ability to
analysis a problem to define its requirements and design both the necessary data structures and the correct algorithm will be applicable to other programming languages and will be very useful for the following programming courses.

Educational objectives

General goals:
The course is aimed at acquiring the basic logical and set-up knowledge to tackle the study of other topics in mathematics and computer science.

Specific goals:

Knowledge and understanding:
At the end of the course student will have full understanding of the proposed logical-set-theoretical tools.

Apply knowledge and understanding:
Students will have acquired the ability to carry out a rigorous, even if elementary, mathematical reasoning, in particular with regard to the fundamental logical principles and the use of induction in all its forms.

Critical and judgmental skills:
Students will therefore be able to critically address the arguments proposed in other theoretical and applied teachings. In this regard, many examples are given from other lessons.

Communication skills:
Active participation in the classroom and the use of the oral exam serve to stimulate students in acquiring the proper language of mathematics and to transmit the knowledge and skills acquired appropriately .

Ability to continue the study:
Students will be able to deepen in the personal study the topics treated using what they have learned as a basis.

Educational objectives

GENERAL GOALS:
This course aims to develop B2-level communicative competence in English. Students will be able to understand and produce more complex texts autonomously and appropriately, on both concrete and abstract topics, across a variety of contexts. The course also aims to consolidate linguistic autonomy and promote active and conscious participation in foreign language communication.
SPECIFIC GOALS:
The course will focus on the main advanced grammatical and lexical structures required to develop the communicative functions defined at the B2 level.
These are the main communicative functions the course aims to develop:
- expressing well-structured opinions, giving reasons, and supporting arguments;
- understanding and participating in complex conversations, even in unfamiliar contexts;
- understanding and summarising the content of complex written and spoken texts.

KNOWLEDGE AND UNDERSTANDING:
By the end of the course, students will have acquired the main grammatical structures, vocabulary, and language functions corresponding to the upper-intermediate B2 level of the Common European Framework of Reference for Languages (CEFR).
APPLYING KNOWLEDGE AND UNDERSTANDING:
By the end of the course, students will be able to understand complex spoken and written texts on both concrete and abstract topics, including technical discussions in their areas of interest. They will also be able to write clear, organised texts and communicate effectively on a wide variety of subjects.
CRITICAL AND JUDGEMENTAL ABILITIES:
Students will be able to independently identify possible language mistakes and evaluate the accuracy and effectiveness of their oral and written texts. Through metacognitive processes, they will develop greater awareness of their language skills and of possible areas for improvement.
COMMUNICATION SKILLS:
Students will be able to communicate more fluently and accurately in various contexts, including formal ones. They will be able to interact with different interlocutors, adapting their language and register. They will know how to express complex ideas in a clear and structured way, both orally and in writing, on a wider range of topics.
LEARNING ABILITY:
The course will help students develop independent learning strategies by using various resources. They will learn to organise their study effectively by setting personal language goals and monitoring their own progress. They will also develop greater awareness of the similarities and differences between English and their native language.

Educational objectives

The teaching consists of two modules: read the objectives of the single module.

Educational objectives

General goals:
Expose students to solid methodologies for the design and implementation of databases in Third Normal Form, along with their related applications.
Specific goals:
Introduce students to formal and scalable methodologies for identifying constraints, performing conceptual analysis, and translating into the relational logical model, leading to the design and implementation of normalized databases and the use of standard technologies for querying them and embedding queries in software applications.
Knowledge and understanding:
Students will acquire fundamental methodological knowledge for designing non-trivial databases, particularly in the phases of:
a) requirements gathering;
b) conceptual analysis of data and functionalities;
c) database and functionality design;
d) verification of normalization and correction of anomalies, if necessary.
They will also learn how to implement these designs using DBMS and standard languages for data definition, querying, and manipulation.
Applying knowledge and understanding:
Students will be able to effectively apply the knowledge described above to real-world projects involving non-trivial database applications.
Critical and judgmental abilities:
Students will be able to independently make rational decisions at all stages of the database and application design process and assess whether a relational schema conforms to Third Normal Form.
Communication skills:
Students will be able to interact effectively with clients (regarding requirements gathering) and with other analysts and designers (regarding the analysis and design of non-trivial software systems).
Learning ability:
Students will be able to independently expand their knowledge by consulting technical documentation as needed in the field of database application design"
Specific goals: to obtain a general knowledge of the basic techniques of Differential Calculus and of the standard applications to problems of maxima-minima of functions of a real variable and to the study of their graph.
Knowledge and understanding: at the end of the course, students will master the basic notions of Differential Calculus, in particular the notions of function, limit and derivative.
Applying knowledge and understanding: students will be able to solve typical problems from Differential Calculus, such as the explicit calculation of derivatives, of maxima and minima of a function, and to plot an approximate graph of functions of a real variable.
Critical and judgmental abilities: students will be able to use a graph as a tool to analyse concrete phenomena which admit a mathematical description.
Communication skills: students will be able to fully understand a scientific text of moderate complexity and relate on the essential ideas contained in it.
Learning ability: the notions and techniques learned will give students access to more advanced notions, either in a further course or in the form of self-study, concerning further aspects of Differential and Integral Calculus.

Educational objectives

General goals:
This course introduces students to basic methods for algorithm design and analysis. They will study well-known algorithms that solve fundamental problems such as sorting or searching, together with the simplest tools to analyze them from an efficiency point of view.
Specific goals
The course aims to make the basic algorithms and fundamental data structures correctly used.
In particular, the main algorithms for solving search and sorting problems will be addressed.
The most important data structures will then be studied: unordered and ordered arrays, simple and double lists, dictionaries, trees.
Finally, the tools for calculating the computational cost of algorithms will be provided.

Knowledge and understanding:
At the end of the course, students will know the basic methodologies for the design and analysis of iterative and recursive algorithms, elementary data structures, the main sorting algorithms and the most basic implementations of dictionaries.
Applying knowledge and understanding:
At the end of the course, students will be familiar with the main basic data structures, particularly those implementing dictionaries. They will be able to explain the algorithms and analyze their complexity, highlighting how performance depends on the data structure used. They will be able to design new data structures and related algorithms, reworking existing ones; will be able to explain the main sorting algorithms, illustrating the underlying project strategies and the related complexity analyses; they will be able to compare the asymptotic behavior of the execution times of the studied algorithms; they will be able to design recursive solutions to problems and asymptotically analyze the resulting algorithms.
Critical and judgmental abilities:
The student will have the basis for analyzing the quality of an algorithm and of the related data structures, both from the point of view of the effective resolution of the
problem and from that of the computational efficiency with which the problem is solved.
Communication skills:
The student will acquire the ability to present his knowledge in a clear and organized way, which will be verified through the questions presented in the written tests and during the oral exam. The student will be able to express an algorithmic idea rigorously at a high level, in pseudocode.
Learning ability:
The knowledge acquired will allow the student to tackle the study of algorithmic techniques and more advanced data structures.

Educational objectives

General goals:
Learning object-oriented programming concepts through the Java programming language.

Specific goals:
Fundamentals of object oriented programming: classes and objects, encapsulation, inheritance, polymorphism, static and dynamic binding, design patterns. Functional programming. Tools and methodologies for software design through an object-oriented programming language. Java language.

Knowledge and understanding:
Knowledge of OOP constructs, with special reference to Java. Understanding a Java program. Ability to write a small- or medium-size Java programs.

Applying knowledge and understanding:
Ability to apply basic methodologies to face software system design of small and medium size. Ability to use the main development tools to implement such systems in Java.

Critiquing and judgmental abilities:
Ability to identify correct/effective and incorrect/ineffective instructions, constructs or patterns in Java.

Communication skills:
Ability to illustrate projects.

Learning ability:
Ability to learn and apply new programming techniques starting from those learned during the course.

Educational objectives

General goals: To learn basic Linear Algebra and Geometry.
Specific goals: Vector spaces, dimension, linear maps, isomorphisms, matrices, elementary operations, reduction to a row echelon matrix.
Affine spaces, affine maps, affine coordinates.Determinant, Laplace, Binet, Cramer.Diagonalization, eigenvalues, eigenspaces.
Positive definite real scalar product. Knowledge and understanding: The student will learn basic Linear Algebra and Geometry.
Applying knowledge and understanding: The student will learn to apply Linear Algebra and Geometry in order to solve problems.
Critical and judgmental abilities: The student will learn when Linear Algebra and Geometry are relevant for the solution of a problem.
Communication skills: The student will learn to communicate using the language of Linear Algebra and Geometry.
Learning ability: The student will be able to understand results in Linear Algebra and Geometry.

Educational objectives

The teaching consists of two modules: read the objectives of the single module.

Educational objectives

General goals: The purpose of the course is to provide the student with basic mathematical analysis tools such as : the theory of series, integral calculus and differential equations.
Specific goals: Students will be able to examine various techniques of integration and apply them to compute definite and indefinite integrals by using integration by substitution and the rule of integration by parts.Students will be able tocompute limits of sequences and discuss the convergence of number series, power seriesand Taylor series of elementary functions.
Knowledge and understanding: At the end of this course the students will be able to calculate integrals and the solutions of some first order differential equationsand the solutions of second order linear differential equations with constant coefficientsLearning activities consists of lectures and exercise sessions. The lecture aim to introduce fundamental concepts, to explain them by showing examples.
Applying knowledge and understanding: The exercise sessions aim to teach how to select and use calculation methods.
Critical and judgmental abilities: To be able to autonomously solve new problems, applying mathematical tools to phenomena or processes to be encountered in University studies or subsequent working activities.
Communication skills: To know how to communicate using properly mathematical language.
Learning ability: To be able to deepen autonomously some arguments introduced during the course.

Educational objectives

General goals:
How to design combinational and sequential circuits.
Specific goals:
binary encoding of different data types, boolean algebra, analysis and synthesis of combinational circuits, flip-flop, analysis and synthesis of sequential circuits, registers,interconnection between register and functional units.
Knowledge and understanding:
Knowing and understanding the handling and processing of information on a computer.
Applying knowledge and understanding:
Show the ability of designing simple combinational and sequential circuits that perform specific tasks.
Critical and judgmental abilities:
Being able to choose the best approach, among those considered, for solving a specific task.
Communication skills:
Being able to evaluate and motivate the choices taken in the design of a circuit.
Learning ability:
Understanding the differences and advantages of the different design techniques.

Educational objectives

General goals:
Expose students to solid methodologies for the design and implementation of databases in Third Normal Form, along with their related applications.
Specific goals:
Introduce students to formal and scalable methodologies for identifying constraints, performing conceptual analysis, and translating into the relational logical model, leading to the design and implementation of normalized databases and the use of standard technologies for querying them and embedding queries in software applications.
Knowledge and understanding:
Students will acquire fundamental methodological knowledge for designing non-trivial databases, particularly in the phases of:
a) requirements gathering;
b) conceptual analysis of data and functionalities;
c) database and functionality design;
d) verification of normalization and correction of anomalies, if necessary.
They will also learn how to implement these designs using DBMS and standard languages for data definition, querying, and manipulation.
Applying knowledge and understanding:
Students will be able to effectively apply the knowledge described above to real-world projects involving non-trivial database applications.
Critical and judgmental abilities:
Students will be able to independently make rational decisions at all stages of the database and application design process and assess whether a relational schema conforms to Third Normal Form.
Communication skills:
Students will be able to interact effectively with clients (regarding requirements gathering) and with other analysts and designers (regarding the analysis and design of non-trivial software systems).
Learning ability:
Students will be able to independently expand their knowledge by consulting technical documentation as needed in the field of database application design.

Educational objectives

General goals:
This course introduces students to methods for designing and analyzing algorithms. Non-elementary data structures will also be covered.
Specific goals:
Students will study various algorithmic techniques widely applicable, such as greedy technique, divide and conquer, dynamic programming, and backtracking. These techniques will be illustrated through classic algorithms such as Dijkstra's algorithm and the Bellman-Ford algorithm for finding shortest paths, Kruskal's algorithm or Prim's algorithm for the minimum spanning tree problem.
Knowledge and understanding:
Upon completion of the course, students will be familiar with methodologies for designing and analyzing algorithms, non-trivial data structures, and key algorithms.
Applying knowledge and understanding:
By the end of the course, students will have gained familiarity with major data structures. They will be able to explain algorithms and analyze their complexity, highlighting how performance depends on the data structure used. Faced with a new problem, they will have various algorithmic techniques at their disposal to reference when seeking an efficient algorithm to solve it.
Critical and judgmental abilities:
Students will have the tools to analyze the quality of an algorithm and its associated data structures, both in terms of effectively solving the problem and the computational efficiency with which the problem is solved.
Communication skills:
Students will acquire the ability to clearly and organizedly present their knowledge, which will be assessed through questions in written exams and during oral exams. They will be able to express algorithmic ideas rigorously at a high level, using pseudocode.
Learning ability:
The knowledge acquired will enable students to tackle problems using more advanced algorithmic techniques and data structures than those covered in the introductory algorithms course.

Educational objectives

"General goals:
The course focuses on operating systems concepts, structure, and mechanisms. Fundamental characteristics, present since the most traditional systems, will be treated, but also peculiarities of modern systems that arise due to the recurring evolution of technology."
"Specific goals:
The course will cover the characteristics and concepts of modern operating systems, with particular reference to Unix and Linux systems. We will start with a description of the evolution of operating systems over time and continue with fundamental concepts such as processes, stalling and related prevention mechanisms, process concurrency, memory management, processor and I/O, files system, and security."
"Knowledge and understanding:
To understand in depth how operating systems support the execution of user programs and manage the hardware peripherals of a computer. Fundamental methods and techniques for in-memory process representation and efficient handling of multiprogramming - multiple processes loaded/running concurrently - on a resource-constrained system."
"Applying knowledge and understanding:
Design user and system-level programs efficiently and securely."
"Critical and judgmental abilities:
To predict the use of resources required by a program, to discover a possible deadlock situation in a multi-programmed system. to ensure mutual exclusion between processes and secure access to memory areas or sensitive resources."
"Communication skills:
Knowing how to clearly and precisely communicate the characteristics of operating systems and their software/hardware support mechanisms."
"Learning ability:
Know how to exploit the knowledge acquired in the design of systems and user programs in the next module of the course. Use this knowledge in learning properties of more complex systems such as distributed and cloud systems."

Educational objectives

General goals:
The goal of the course on Computer Architecture is to make students understand the principles used to design modern computers. In particular, the course deals with the internal structure of the microprocessor and the ideas that have allowed the extraordinary evolution of computing power over the last 30 years. such as pipelining, caching, branch prediction, and multi-processing.
Specific goals:
The course covers the basic principles of microprocessor organization and the concepts of pipelining, caching, branch prediction, virtualization and multi-processing. Furthermore, the course covers assembly programming.
Knowledge and understanding:
Students will acquire knowledge about the organization of the RISC microprocessor, as implementation of the general ideas that are part of the objectives of the course. Furthermore, the student will acquire knowledge on how the assembly programs are structured, including data structures, standard programming paradigms and recursion.
Applying knowledge and understanding:
The knowledge is applied to the MIPS architecture, enabling students to understand the implications of programming choices on the performance of programs on specific hardware. This result is obtained through programming and performance evaluation exercises.
Critical and judgmental abilities:
The student will be able to understand the problems related to the performance of the software on specific hardware and to independently evaluate their characteristics.
Communication skills:
The course is not concerned with explicit objectives on communication skills, except to instruct on the rigorous presentation of formal topics.
Learning ability:
The course lays the foundations for the comprehension of the modules constituting the course of Operating Systems and of all the courses of programming, including the programming of parallel systems.

Educational objectives

General goals:
- Learn the fundamentals of modern computer networks and Internet

Specific goals:
Knowledge and understanding:
- Application, transport, network, and data-link protocols of the TCP/IP model

Applying knowledge and understanding:
- Understand any protocol involved with TCP/IP communications
- Grasp powerful network troubleshooting tools and techniques
- Ability to use network services like DNS and DHCP that help make computer networks run

Autonomy of judgment:
- Detect network problems
- Evaluate the design of new services

Communication skills:
- Ability to describe computer networks in terms of a five-layer model

Learning ability:
- The course provides the fundamentals to learn notions related to wireless systems and Internet of Things

Educational objectives

General Goals
To create complex software systems that are reliable and efficient may require the programmer to directly exploit the operating system support for the manipulation of resources such as processes, memory, the file system and I/O devices, synchronization between concurrent processes and communication between processes running on remote nodes. Error-free programming and correct handling of exceptions at runtime leads to the creation of reliable systems. While profiling a program at runtime, that is, observing the resources it uses (e.g. memory) and the execution time allows one to understand how efficient a program is and to choose the most performing data structures and algorithms for the realization of a task.
The "Advanced Programming" course aims to provide the student with the knowledge necessary for the development of reliable and efficient software.

Specific goals:
In particular, the student will learn:
● To create programs using compiled languages such as C, Rust and C++

● To program using the operating system support through the interface it provides, i.e.
system calls (and library functions)
● To develop programs that are able to create processes (or threads), access system
resources (file system and I/O), communicate with other processes (sockets, pipes),
synchronize with other processes (signals, semaphores, mutexes) to access shared
resources (memory, file system, I/O)
● To create reliable and efficient programs
● To identify, prevent and manage errors at runtime
● To trace the behavior of a program in execution
Knowledge and understanding:
● To understand in depth how operating systems support the execution of user programs
and manage the hardware peripherals of a computer.
● To understand and use fundamental methods and techniques for representing
processes in memory and the efficient management of multiprogramming.
● To understand the use of programming languages such as C, Rust, C++ and the main
Linux system calls.
Applying knowledge and understanding:
Design reliable and efficient user-level and system-level programs
Critical and judgment skills:
Be able to predict the use of resources required by a program, discover deadlock situations in a
multiprogrammed system, ensure mutual exclusion between processes and protected access to
memory areas or shared resources. Determine which programming language is best suited,
among those studied, to achieve given reliability or efficiency objectives.
Communication skills:
Be able to communicate clearly and precisely
● the mechanisms for accessing the operating system API
● how to create reliable and secure programs
● how to identify, prevent and manage errors at runtime, and trace the behavior of a
program in execution
Learning ability:
● To exploit the knowledge acquired in the design of reliable and secure systems.
● To learn the properties of more complex systems such as distributed and cloud systems.

Educational objectives

General objectives:
The course aims to provide fundamental knowledge and application skills in the main topics of probability and statistics.

Specific objectives:
Acquire the fundamental concepts of probability theory and the main distributions of discrete and continuous random variables, understand the concepts of expected value, independence, conditioning, and the basic principles of statistical inference, learn the concepts of convergence for sequences and series of real and trigonometric functions, with attention to uniform convergence and mean-square convergence, gain knowledge of the essential elements of the theory of functions of a complex variable, including holomorphy, singular points, and residues, understand the application of the Laplace and Fourier transforms.

Knowledge and understanding:
By the end of the course, students will have acquired the basic concepts and results related to probability theory on finite and countable spaces, the concept of discrete random vectors, and the concept of continuous random variables.
They will also have learned the fundamentals of approximation theory and the basics of statistics.

Applying knowledge and understanding:
By the end of the course, students will be able to solve simple problems in discrete probability, problems related to discrete random vectors, and random numbers represented by continuous random variables.
They will also be able to appreciate the meaning and implications of independence and conditioning (within discrete models).
Additionally, they will be able to apply the Laplace transform and use the Fourier transform on appropriate classes of functions.

Critical and judgment skills:
Students will develop the ability to construct probabilistic models in simple application contexts of physical, biological, and technological interest, to use tables and simulation software for the most commonly applied discrete laws, and to understand the use of basic statistical tools in inference, statistical sampling, and simulation.

Communication skills:
The acquired knowledge will allow students to clearly and rigorously present the learned contents, responding effectively to theoretical and practical questions, both in the written and oral examinations.

Learning skills:
The skills developed will support independent study or further study through specialized courses in advanced aspects of probability and statistics.

Educational objectives

General goals:
The course introduces the students to some of the most important results in theoretical computer science: from the fundamental results in computability theory of the thirties, through the ones in automata theory of the fifties to the challenging open problem P versus NP, raised in the seventies.

Specific goals:
Students will understand that there are different models of computation and the reason for their different computational power.

The students will become familiar with abstract concepts such as language classes, universal machines, reducibility and they will know that some problems are impossible to solve by computers and that others are difficult to solve, even so difficult to solve that they could be considered unsolvable. They will see today's use of some of these results.

Knowledge and understanding:
By the end of the course the students will get familiar with the basic methods and results of the Theory of Computability and Complexity and they will be able to apply them to evaluate the complexity of problems from various fields. In particular, they will be able to:
prove the equivalence between different characterizations of regular languages
prove the equivalence between different characterizations of context-free languages
explain the concept of nondeterminism
explain the existence of problems without algorithmic solutions or those which are intractable

Applying knowledge and understanding:
By the end of the course the students will be able to:
build finite state automata by a formal or an informal specification of a language
build stack automata by a formal or an informal specification of a language
use reducibility between problems to prove either decidability or undecidability
use polynomial reductions to prove the NP-hardness of problems.

Critical and judgmental skills:
Understand the right level of abstraction to solve problems, choose the more convenient computational model in an applicative context.

Communication skills:
describe problems that are undecidable, not provably intractable or intractable
explain the meaning and the relevance of the question “P=NP?"

Learning ability:
The student will be able to learn other computational models, both really new or variations of the ones seen during the course. She/he will be able to understand new NP-completeness proofs or more generally completeness proofs for any complexity class.

Educational objectives

General objectives:
The course explains the fundamentals of the methodologies and tools for the management of software processes. Particular attention is given to object-oriented analysis and design methodologies, and to their management and documentation through UML.

Specific objectives:
Introduction to software engineering approaches and software life cycle, in-depth analysis of the specific activities, analysis, design and testing of software systems, techniques for process management, with particular reference to the management of quality and risks and all 'cost analysis.

Knowledge and understanding:
At the end of the course students will have acquired knowledge about the main models of the software life cycle, the metrics for the sizing of the effort, the techniques for describing the different components of a software project. Knowledge about the use of UML language will have been acquired. Finally, they will also have become familiar with the scientific literature in the field.

Application of knowledge and understanding:
At the end of the course students will be able to work as a team in the activities of analysis, design, documentation and management of medium-sized software projects. Students will have learned to produce documentation based on UML, relative to the main types of diagrams: use cases, classes, interaction, status and activities, also through the use of professional software environments oriented to the systematic development of software projects. Finally, they will be able to produce an evaluation of the effort based on Function Points and Use Case Points.

Judgment skills:
Students will develop the analytical skills necessary to evaluate various alternatives during the software development process, with particular reference to the evaluation of architectural choices and project risks.

Communication skills:
Students will learn to document their choices, also through the use of documentation generation tools, in particular by exploiting diagrammatic notations. They will also have acquired the ability to prepare presentations related to scientific topics.

Learning ability:
The knowledge of the formal rigor aspects underlying the software engineering discipline will allow students to quickly gain confidence with techniques, in addition to those considered in the course, based on general principles.

Educational objectives

AT THE STUDENT'S CHOICE

Educational objectives

The internship is carried out under the guidance of a manager and can be external (performed at companies or external bodies) or internal (carried out within the degree course). In both cases, the internship lasts about three months and requires that the student be offered a problem in the real world, to be solved through the elaboration of a project developed with a professional approach.

Educational objectives

The final exam consists in the drafting, presentation and discussion of a written dissertation, prepared independently by the student, which documents in an organic and detailed way the problem faced in the training internship and all the activities performed to reach the solution.