ID:
T046
Tipo Insegnamento:
Obbligatorio
Durata (ore):
48
CFU:
6
SSD:
INFORMATICA
Url:
ECONOMICS AND BUSINESS/BASE Anno: 2
Anno:
2023
Dati Generali
Periodo di attività
Primo Semestre (11/09/2023 - 02/12/2023)
Syllabus
Obiettivi Formativi
The course is focused on the fundamental topics of Computational thinking and Python programming. In particular, the course objectives are twofold:
-Theoretical aspects, including the main concepts of Computational thinking to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that students should possess to keep ahead of the curve in this modern era of information technology. In fact, developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence.
Practical capacity to develop software in Pyhton language.
-Theoretical aspects, including the main concepts of Computational thinking to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that students should possess to keep ahead of the curve in this modern era of information technology. In fact, developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence.
Practical capacity to develop software in Pyhton language.
Prerequisiti
ECDL diploma or equivalent knowledge certified by Luiss.
Metodi didattici
Traditional and Reverse teaching
Verifica Apprendimento
The student will be evaluated on the basis of the individual scores achieved on: home exercises and final exam. The written test consists of a mix of open-ended questions, multiple choice questions and exercises, with which the student have to demonstrate knowledge of the theoretical notions of teaching, knowing how to apply them in practical cases demonstrating that he has achieved the method of study and the learning ability necessary to continue the study of the subject autonomously.
The failure to achieve at least the score of 18/30 will result in failure to pass the exam.
Correct answers to all multiple-choice questions, an excellent level of preparation in all open questions and the correct execution of all the exercises will result in a score of 30/30 cum laude.
The failure to achieve at least the score of 18/30 will result in failure to pass the exam.
Correct answers to all multiple-choice questions, an excellent level of preparation in all open questions and the correct execution of all the exercises will result in a score of 30/30 cum laude.
Testi
Title:
Python Programming and Numerical Methods, A Guide for Engineers and Scientists, 1st Edition -
Qingkai Kong, Timmy Siauw, Alexandre Bayen
No. of pages: 480
Language: English
Copyright: Academic Press 2020
Published: November 27, 2020
Imprint: Academic Press
Paperback ISBN: 9780128195499
eBook ISBN: 9780128195505
Further readings will be available on the elearning platform of the course.
Contenuti
The course will be split in two main parts: Computer systems and networks
as the theoretical part and Python training as Laboratory part.
The former part will be focused on Computational thinking and Python language, with a preliminary introduction of the fundamental elements of computer science, including theory, design, computational processes and systems, and computers. Then, with Elements of Computational Thinking, the course will aim to explain each of the elements of computational thinking—decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design—and how the process of computational thinking is not linear. Rather, a developer can go back through some of these elements at all stages of the algorithm design process until a solution for a particular problem is reached. The course will introduce Understanding Algorithms and Algorithmic Thinking, providing the students you with an introduction to algorithms and their definition. We will also review some algorithms to help the students develop the analysis skills necessary when assessing algorithms.
The course will be briefly cover Understanding Logical Reasoning, exploring logical reasoning processes such as conditional statements, algorithmic reasoning, and Boolean logic. Further knowledge on Algorithm Complexity and Representation of Numbers will complete the computational thinking section before starting with Python language Variables and Basic Data Structures, Functions, Branching Statements, Iteration, Recursion, Object Oriented Programming (OOP), Errors, Good Programming Practices, and Debugging.
The latter part will deliver the lab skills to develop software autonomously, with Python IDE, packages and many exercises of practical applications, particularly focused on microeconomics.
Risultati di Apprendimento Attesi
Knowledge and understanding: The student will learn to–
Find out how to use decomposition to solve problems through visual representation
Employ pattern generalization and abstraction to design solutions
Build analytical skills required to assess algorithmic solutions
Use computational thinking with Python for microeconomic analysis
Understand the input and output needs for designing algorithmic solutions
Use computational thinking to solve data processing problems with Python
Identify errors in logical processing to refine their solution design
Apply computational thinking in various domains, such as microeconomics, and statistics
At the end of the course there will be a written test.
Applying knowledge and understanding: The student - acquiring the correct tools and method - will be able to understand how to computationally solve basic problems and how to design and develop the related Python software. At the end of the course there will be a written test.
Making judgements: The student, through the use of the methodologies acquired during the course, will have acquired problem analysis skills and the ability to autonomously craft python software for their solution. Specifically, critical and computational thinking, problem solving, self-management, and communication skills will be adequately developed, which enhance and make the disciplinary skills more usable.
Communication skills: At the end of the course the student will be able to use the business and technical vocabulary of IT, of the Internet technology. Through the various activities that will take place during the course – lessons with discussion, laboratories, workshops – the student will be able to put these communication skills into practice in various contexts, by adapting the terms used to the interlocutor in the specific case, thus gaining advanced rhetorical skills necessary for his/her professional career.
Learning skills: The technical- knowledge acquired during the course will allow the student to autonomously understand and solve basic problems via software development. The student will develop a solid knowledge of the fundamental aspects of the subject that will allow her/him to continue to deepen the topics addressed independently and to undertake the various post-graduate Computer Science training courses.
Criteri Necessari per l'Assegnazione del Lavoro Finale
Top level mark in the course /good knowledge in some computer systems
topics (although out of the scope of the course) constitute a prerequisite for
final paper assignment.
Corsi
Corsi
ECONOMICS AND BUSINESS
Laurea
3 anni
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Persone
Persone
Altro personale docente
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