Study-unit
| Course name | Computer science and electronic engineering |
|---|---|
| Study-unit Code | A003495 |
| Curriculum | Ingegneria informatica |
| CFU | 6 |
| Course Regulation | Coorte 2022 |
| Supplied | 2023/24 |
| Supplied other course regulation | |
| Type of study-unit | Obbligatorio (Required) |
| Type of learning activities | Attività formativa integrata |
| Partition |
| Code | A003496 |
|---|---|
| CFU | 3 |
| Lecturer | Giuseppe Baruffa |
| Lecturers |
|
| Hours |
|
| Learning activities | Affine/integrativa |
| Area | Attività formative affini o integrative |
| Sector | ING-INF/03 |
| Type of study-unit | Obbligatorio (Required) |
| Language of instruction | The course is held in Italian. |
| Contents | MATLAB/Octave language programming, using MATLAB/Octave in data and signal processing when interacting with systems. |
| Reference texts | Suggested textbooks: * A. Corbellini, F. Laurini, D. Perrotta, M. Riani, F. Torti, “Data Science con MATLAB”, I ed., pp. 1.464, ISBN: 978-8892124400, Giappichelli Editore, Settembre 2022 * M. Scarpiniti, “Laboratorio di Programmazione: MATLAB per l'Ingegnere dell'Informazione”, Versione 1.8, pp. 1-722, ISBN: 979-8689225487, Self-published, Amazon KDP, Settembre 2020. |
| Educational objectives | Understanding the syntax and logical operation of a MATLAB/Octave program. Being able to write a MATLAB/Octave program to analyze and model data, signals, and systems. |
| Prerequisites | None. |
| Teaching methods | Face to face lessons of theoretical arguments are held using a PC with digital projector; integrations are developed using the (multimedia) blackboard. Each lesson also includes a part of computer exercises. For information on support services for students with disabilities and/or SLD, visit the page https://www.unipg.it/en/international-students/general-information/facilities-for-special-needs-students. |
| Other information | Further information will be available in the UniStudium webpage dedicated to this course, which is accessible to all the students enrolled in this course. |
| Learning verification modality | The examination consists of a written exam with questions and multiple answers (or equivalent) on the arguments introduced during the lessons, conditionally followed by a practical exercise at a computer terminal (or another equivalent method). If the student intends to take the exam in a year prior to that scheduled in the study plan, it is recommended to attend the cycle of lectures and to take the exam in the first available session after the lessons have ended, respecting the planning semester. |
| Extended program | General Section: introduction to the development environment; basics of the MATLAB/Octave language; acceleration of matrix and tensor calculus; parallelization; visualization; programming with Simulink; advanced object-oriented programming. Case studies: acquisition and analysis of signals, sounds, and images; optimization problems; PAM wave simulation; dynamical systems and transforms; statistical data processing. |
| Obiettivi Agenda 2030 per lo sviluppo sostenibile |
| Code | A003497 |
|---|---|
| CFU | 3 |
| Lecturer | Gabriele Costante |
| Lecturers |
|
| Hours |
|
| Learning activities | Affine/integrativa |
| Area | Attività formative affini o integrative |
| Sector | ING-INF/04 |
| Type of study-unit | Obbligatorio (Required) |
| Language of instruction | The course is held in Italian. |
| Contents | Python language programming, use of development environments for data and signal processing when interacting with systems. Code and program implementation for application case studies. |
| Reference texts | Suggested textbooks: * Downey, A. Think python. " O'Reilly Media, Inc.". * McKinney, W. Python for Data Analysis. " O'Reilly Media, Inc.". * Lynch, S. Dynamical systems with applications using python. Switzerland: Springer International Publishing. |
| Educational objectives | Understanding the syntax and logical operation of a Python program. Being able to write a Python program to analyze and model data, signals, and systems. |
| Prerequisites | None. |
| Teaching methods | Face to face lessons of theoretical arguments are held using a PC with digital projector; integrations are developed using the (multimedia) blackboard. Each lesson also includes a part of computer exercises. For information on support services for students with disabilities and/or SLD, visit the page https://www.unipg.it/en/international-students/general-information/facilities-for-special-needs-students. |
| Other information | Further information will be available in the UniStudium webpage dedicated to this course, which is accessible to all the students enrolled in this course. |
| Learning verification modality | The examination consists of a written exam with questions and multiple answers (or equivalent) on the arguments introduced during the lessons, conditionally followed by a practical exercise at a computer terminal (or another equivalent method). If the student intends to take the exam in a year prior to that scheduled in the study plan, it is recommended to attend the cycle of lectures and to take the exam in the first available session after the lessons have ended, respecting the planning semester. |
| Extended program | General Section: introduction to the development environment; basics of the Python language; matrix and tensor calculus; parallelization; visualization; usage of the pandas library for input/output functionalities and data processing; advanced object-oriented programming. Case studies: acquisition and analysis of signals, sounds, and images; optimization problems; PAM wave simulation; dynamical systems and transforms; statistical data processing. |
| Obiettivi Agenda 2030 per lo sviluppo sostenibile |