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 is 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 (digital resource).
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 (digital resource).
2. PHILLIPS, Dusty. Python 3 object oriented programming: harness the power of Python 3 objects. 1st ed. Birmingham, UK: Packt Open Source, 2010. ISBN 9786612712487, 9781282712485, 1282712489, 9781849511278, 1849511276, 9781849511261, 1849511268 (digital resource).
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, CE2, TR2 and TR3.
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.
Although all the activities scheduled during the semester contribute jointly to the acquisition of the skills mentioned above, the main relationships between the two are specified below:
1. Theory sessions (competencies CG1, CG4, CB3) 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. Practical individual activities (competencies CG2, CG3, CB2, TR3, CE2). In the computer lab, students will complete five interactive programming exercise sets of increasing length and complexity.
3. Follow-up and feedback (competency TR2). 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 (competencies CB4, CB5). At the end of the semester, students must individually demonstrate the level achieved with respect to the competencies of the subject through a theoretical-practical exam that will take place on the officially approved date.
The specific schedule of activities will be made available before the start of the semester through the Virtual Campus.
USC’s specific regulations for student performance assessment and mark review will apply as soon as academic fraud is exposed. Students are expressly warned that software submitted for evaluation may be subject to analysis using high-quality, semi-automatic plagiarism detection tools.
First opportunity: the evaluation will be carried out according to the following weighting distribution: 30% for the final theoretical-practical exam and 70% for the programming reports. The evaluation of the reports will be carried out on a mixed basis, with half of the grade based on the quality of the work itself and the other half derived from a written test on the contribution. Only the last three reports will be considered for continuous assessment, which must be submitted after the seventh, tenth, and twelfth interactive sessions, respectively. Furthermore, it should be noted that to pass the course, a minimum score of four points is required on both the exam and the practical work.
It is explicitly stated that attendance at the interactive sessions of this subject is essential for achieving its goals, so absences must be adequately justified.
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. In relation to the provisions of the first article, on the evaluation systems, of the Regulations for class attendance in official undergraduate and master's courses at the University of Santiago de Compostela, it is stated that class attendance will not be directly taken into account in the student's evaluation.
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.
Planned activities will be supported by USC’s Virtual Campus (Moodle platform) and Microsoft Teams, mainly.
On the other hand, 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
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
Alejandro González Santos
- Department
- Electronics and Computing
- Area
- Languages and Computer Systems
- alejandrogonzalez.santos [at] usc.es
- Category
- Xunta Pre-doctoral Contract
| 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 | Spanish | IA.12 |
| Thursday | |||
| 09:00-11:30 | Grupo /CLIL_02 | Galician, Spanish | IA.12 |
| 01.16.2026 09:15-14:00 | Grupo /CLE_01 | IA.01 |
| 01.16.2026 09:15-14:00 | Grupo /CLIL_01 | IA.01 |
| 01.16.2026 09:15-14:00 | Grupo /CLIL_03 | IA.01 |
| 01.16.2026 09:15-14:00 | Grupo /CLIL_02 | IA.01 |
| 01.16.2026 09:15-14:00 | Grupo /CLIL_01 | IA.02 |
| 01.16.2026 09:15-14:00 | Grupo /CLIL_03 | IA.02 |
| 01.16.2026 09:15-14:00 | Grupo /CLIL_02 | IA.02 |
| 01.16.2026 09:15-14:00 | Grupo /CLE_01 | IA.02 |
| 06.18.2026 09:30-14:00 | Grupo /CLE_01 | IA.01 |
| 06.18.2026 09:30-14:00 | Grupo /CLIL_01 | IA.01 |
| 06.18.2026 09:30-14:00 | Grupo /CLIL_03 | IA.01 |
| 06.18.2026 09:30-14:00 | Grupo /CLIL_02 | IA.01 |