Computer Science

This course is part of the Laurea Magistrale degree program and is intended for advanced level students. Enrollment is by permission of the instructor. This course provides students with the advanced knowledge to the field of network analysis and its usages in other fields of research. At the end of the course, students gain knowledge on the Web as a socio-technical system involving specific processes, entities, and behaviors, using interdisciplinary methods that blend computer science, sociology, ethnography, economics, linguistics, etc. The students are able to analyze the Web phenomena similarly to typical objects from natural sciences, distinguishing between data and applications, agents from computationally generated profiles, and addressing the characteristics of networks of entities emerging from the informational, physical, social, and conceptual spaces constituting the Web.

This course examines the changing role of the operating system, the concept and implementation of process, the OS/hardware interface with regard to storage and protection, and the techniques developed to achieve safety and throughput in multitasking systems.

1) Teach the essence of software and the basic ideas and the main methods of software engineering systematically based on software lifecycle. 2) Organize the students to develop new software systems of medium size in groups by adopting a new generation of information technology and the new application mode. Guide the students to apply software engineering principles, methods, techniques and tools for software development, management and maintenance. 

This course provides a comprehensive introduction to the modern study of computer algorithms. The course uses Python language as a tool to learn various algorithms in depth. Knowledge in mathematics, especially algebra, is expected and having basic knowledge and experience in Python helps to better understand class content.

This course introduces the fundamentals of understanding user needs, designing prototypes, and evaluating user interfaces. It explores principles, techniques, and tools to create effective and intuitive interfaces, with a special focus on using AI tools. Students of all levels in design and coding skills are welcome. 

This course explores the theory of automata and formal languages. Topics include: automata theory; finite automata; languages and formal grammars; regular languages; pushdown automata; Turing machine; compilers. Pre-requisites: Programming; Programming Techniques.

This course covers programming language concepts, not as paradigms but as a set of basic building blocks, by using the Scala programming language to implement interpreters for the concepts. 

Students will learn how to learn new languages quickly and how to evaluate various languages and pick the most suitable one for a given task. The course also explores how to know when and how to design language, and how to understand the effects of languages on thought and communication. 

This course offers an introduction to computer science with topics including: basic constructions of structured programming; procedural abstractions; structured data types; text files; use of programming and development environments; documentation, testing, and debugging of programs; lab practice. 

This course offers an introduction to Python programming following the structured and object-oriented paradigms. Topics include: flow diagrams; data, operators, input, and output; flow control--conditionals and loops; simple data structures; functions; object oriented programming; algorithms, recursion, and computational complexity.

The course introduces the basic concepts of discrete mathematics needed for the study of computer science. Student learn to work with sets, relations, functions, recursive structures, graphs, trees, basic combinatorial principles, discrete probability, finite automata, and regular languages.