ECTS credits ECTS credits: 6
ECTS Hours Rules/Memories Hours of tutorials: 1 Expository Class: 20 Interactive Classroom: 30 Total: 51
Use languages Spanish, Galician
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Departments: Electronics and Computing
Areas: Languages and Computer Systems
Center Higher Technical Engineering School
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
This course introduces students to the field of imperative programming, presenting basic concepts such as algorithm, program, instruction, data type, variable, operator, conditional and repetitive structures, top-down and bottom-up approaches, function, or library. The proposed activities provide students with a conceptual and technological base on which to develop future Artificial Intelligence (AI) projects. Given its great versatility, its growing popularity and the high availability of modules that facilitate the construction of software by bottom-up approximation, the Python programming language will be used.
Imperative paradigm.
Data types and variables.
Import and use of libraries.
Program control.
Data collections.
Input and output.
Scripts and program testing.
Modular design.
No class notes are provided by the professors in this subject.
Basic Bibliography:
1. MARZAL VARÓ, Andrés, GRACIA LUENGO, Isabel, GARCÍA-SEVILLA, Pedro. Introducción a la programación con Python 3. Universitat Jaume I, 2014. ISBN 9788469711781. DOI http://dx.doi.org/10.6035/Sapientia93. URI http://hdl.handle.net/10234/102653.
2. CUEVAS ÁLVAREZ, Alberto. Python 3. Curso Práctico. Madrid: RA-MA Editorial, 2016. ISBN 9788499643595 (recurso electrónico).
Complementary Bibliography:
1. MCKINNEY, Wes. Python for data analysis: data wrangling with Pandas, NumPy, and IPython. 2nd ed. Sebastopol, CA: O'Reilly Media, Inc., 2018. ISBN 9781491957639, 1491957638, 9781491957615, 1491957611 (recurso electrónico).
2. VANDERPLAS, Jacob T. Python data science handbook: essential tools for working with data. 1st ed. Sebastopol, CA: O'Reilly Media, Inc., 2016. ISBN 1491912146, 9781491912140, 9781491912133, 1491912138, 9781491912041, 1491912049 (recurso electrónico).
To contribute to obtaining the following basic, general, specific and transversal competences included in the official report of the Degree in Artificial Intelligence (GrIA) of the USC, the UDC and the UVigo: CB2, CB3, CB4, CB5, CG1, CG2, CG3 , CG4, CE3, CE4, CE5, TR2, TR3 and TR6.
As a part of GrIA’s Software and Databases module, the expected learning outcomes in this course are:
- To carry out the process that allows, starting from a high level of abstraction, to implement high-quality code.
- To apply modular programming techniques to solve specific problems in the field of AI.
- To understand the syntax and semantics of the programming language used.
- To acquire skills to solve problems both methodologically and practically.
- To identify and have the ability to select in a practical environment the main libraries in the field of AI and Data Science.
- To analyse the alternatives to face a problem and identify which aspects can be addressed with AI techniques.
- To handle test techniques and tools to ensure the quality of the results.
The activities that will be carried out during the semester are the following:
1. Theory sessions focused on the presentation by the professor of the basic concepts of the subject. Theoretical explanations will be interspersed with the proposal and resolution of small-calibre programming exercises.
2. Realization of practical activities individually or in pairs in the computer room. Students will have to face the interactive resolution of different sets of exercises that will contribute to the continuous evaluation of the subject.
3. Follow-up and feedback. On-demand tutorials will be scheduled for the active orientation of the students' work, with special attention to the development of the exercises proposed in the computer room. The face-to-face modality will be combined with the telematic one through Microsoft Teams.
4. Evaluation by examination. During the semester and by its end, students must individually demonstrate the level reached with respect to the competencies of the subject.
Planned activities will be supported by USC’s Virtual Campus (Moodle platform) and Microsoft Teams, mainly.
USC’s specific regulations for student performance assessment and mark review will apply as soon as academic fraud is exposed.
First opportunity: the evaluation will be fully carried out continuously throughout the semester, with weights of 30% and 70% for the theoretical and practical parts, respectively. On the theoretical side, the students will have to face one or several tests, while on the practical level, they will have to develop different programs of increasing size and complexity. To pass the subject, it is necessary to obtain a mark equal to or greater than 5 in the sum of the contributions of theoretical and practical activities.
Article 34 of USC’s Statutes (2014) states that one of the duties of students is to study and actively participate in academic activities that help complete their training, while article 130 contemplates the obligation of attendance and participation in those training activities that are established as compulsory in the teaching programming of the subjects. Article 10 of USC’s Student Statute (2019) further states that students must attend theoretical and practical classes and carry out the training activities of each subject. In this sense, it is explicitly stated that attendance at the interactive sessions of this subject is mandatory, so absences must be adequately justified. Failure to comply with this requirement can lead to strong penalties in the continuous evaluation of the student.
Second opportunity: the evaluation will be based on a theoretical test (30% global weight) and a programming exam (70% global weight).
Anyone who does not take any of the continuous assessment activities that are carried out throughout the semester, nor the second opportunity examinations will be considered Not Presented.
Under no circumstances will marks be kept for following academic years.
The subject is assigned 6 ECTS, which means a personal contribution of approximately 100 hours besides the face-to-face work in the classroom.
There is no special recommendation but regular class attendance and acceptance of the necessary effort to bring the subject up to date. No assumption is made about students' prior knowledge.
Only the installation of the Python interpreter is required on the student's machine. The standard distribution is available at https://www.python.org/.
This subject is taught both in Spanish and Galician.
Julian Carlos Flores Gonzalez
- Department
- Electronics and Computing
- Area
- Languages and Computer Systems
- Phone
- 881816456
- julian.flores [at] usc.es
- Category
- Professor: University Lecturer
Raquel Dosil Lago
- Department
- Electronics and Computing
- Area
- Languages and Computer Systems
- Phone
- 881815507
- raquel.dosil [at] usc.es
- Category
- Professor: LOU (Organic Law for Universities) PhD Assistant Professor
Jose Varela Pet
Coordinador/a- Department
- Electronics and Computing
- Area
- Languages and Computer Systems
- jose.varela.pet [at] usc.es
- Category
- Professor: Temporary PhD professor
| Monday | |||
|---|---|---|---|
| 10:00-11:00 | Grupo /CLE_01 | Spanish | IA.11 |
| 12:00-14:30 | Grupo /CLIL_01 | Spanish | IA.12 |
| Wednesday | |||
| 11:00-12:00 | Grupo /CLE_01 | Spanish | IA.11 |
| 12:00-14:30 | Grupo /CLIL_03 | Galician | IA.12 |
| Thursday | |||
| 09:00-11:30 | Grupo /CLIL_02 | Spanish | IA.12 |
| 01.17.2025 09:00-14:00 | Grupo /CLIL_01 | IA.01 |
| 01.17.2025 09:00-14:00 | Grupo /CLIL_02 | IA.01 |
| 01.17.2025 09:00-14:00 | Grupo /CLIL_03 | IA.01 |
| 01.17.2025 09:00-14:00 | Grupo /CLE_01 | IA.01 |
| 01.17.2025 09:00-14:00 | Grupo /CLIL_03 | IA.11 |
| 01.17.2025 09:00-14:00 | Grupo /CLIL_01 | IA.11 |
| 01.17.2025 09:00-14:00 | Grupo /CLE_01 | IA.11 |
| 01.17.2025 09:00-14:00 | Grupo /CLIL_02 | IA.11 |
| 01.17.2025 09:00-14:00 | Grupo /CLIL_01 | IA.12 |
| 01.17.2025 09:00-14:00 | Grupo /CLIL_02 | IA.12 |
| 01.17.2025 09:00-14:00 | Grupo /CLE_01 | IA.12 |
| 01.17.2025 09:00-14:00 | Grupo /CLIL_03 | IA.12 |
| 06.23.2025 09:00-14:00 | Grupo /CLIL_02 | IA.11 |
| 06.23.2025 09:00-14:00 | Grupo /CLE_01 | IA.11 |
| 06.23.2025 09:00-14:00 | Grupo /CLIL_03 | IA.11 |
| 06.23.2025 09:00-14:00 | Grupo /CLIL_01 | IA.11 |