This course has a twofold objective: on one hand, to introduce to the student to the “cultural” and technological issues related to computer science. On the other hand, the course aims at teaching the use of a computer programming language as a way to solve realistic problems.

Students must acquire two fundamental types of knowledge: (i) the ability to solve concrete problems through programs to be implemented in a programming language and executed on a computer; (ii) the ability to understand quantitative aspects of computer science such as performance, computational capacity, information representation, and computer organization. These skills are applied to solving problems of practical relevance.

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Theory [3 hours] - Information representation Problem Solving and Algorithms [7 hours] - Flow charts and pseudocode for solving complex real-world problems Python Programming Language [30 hours] - Primitive data types - Numeric variables and constants - Strings and string methods - Input and output of numeric data and strings - Elementary arithmetic operators, powers, mathematical functions - Boolean variables and operators - Control flow constructs (conditional and iterative) - Functions and parameter passing - Lists, Sets, Dictionaries - Complex structures (dictionaries of sets and dictionaries of lists) - Reading and writing text files

The course includes approximately 20 hours of laboratory exercises in which topics discussed in class will be translated into Python programs.

Students attend 3 hours of lectures/classroom exercises and 1.5 hours of laboratory work per week (laboratories begin in week two). Instruction is organized into three modalities: - Theory: Introduction to theoretical concepts with accompanying exercises - PPS (Problem Posing & Solving): Analysis of comprehensive problems (e.g., exam-style questions), in-class discussion, and solution design using flow charts or pseudocode (potentially of greater complexity than the programming skills acquired to date). Progressive implementation of increasingly substantial problem components in Python throughout the semester - Programming: Instruction on Python language constructs with live coding demonstrations Each week, students receive: - Learning objectives for the week - Textbook chapters/sections covered in class - Textbook chapters/sections for self-study - Laboratory assignments - Practice exercises from the textbook for self-study - Theory and programming lecture slides - PPS problem case study

Course Materials - Python for Everyone (3rd Edition), Cay S. Horstmann and Rance D. Necaise, Wiley, ISBN 978-1119498537, https://www.wiley.com/en-us/Python+For+Everyone,+3rd+Edition-p-9781119498537

Slides; Libro di testo; Esercizi;

Modalita di esame: Prova scritta in aula tramite PC con l'utilizzo della piattaforma di ateneo;

Exam: Computer-based written test in class using POLITO platform;

... The exam consists of a computer-based test designed to assess students' knowledge of both the theoretical aspects of the subject (through numerical exercises or multiple-choice questions) and the programming component (through the implementation of one or more Python programs that solve practical problems). The written test lasts 1.5 hours and students are not permitted to use any course materials. The maximum grade for the written test is 30 cum laude.

Gli studenti e le studentesse con disabilita o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unita Special Needs, al fine di permettere al/la docente la declinazione piu idonea in riferimento alla specifica tipologia di esame.