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: Computer Science and Artificial Intelligence
Center Higher Technical Engineering School
Call: Second Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
In this course, students will develop the necessary skills to decide with criteria the combination of data structures (linear or trees) and algorithms most convenient to solve a given problem efficiently in terms of spatial and temporal resources. In addition, the course introduces the functional programming paradigm, its characteristic data structures, and fields of application, emphasizing those where approaches and resolutions are easier to achieve than with other programming paradigms.
Algorithms and data structures. Linear data structures (stacks, lists and queues). Trees. Lambda calculus. Functional programming.
Básica:
Algoritmos y estructuras de datos en Python: un enfoque ágil y estructurado / Walter Bel. - 1a ed. - Paraná: Editorial Uader, 2020. ISBN 978-950-9581-60-9. https://editorial.uader.edu.ar/catalogo/algoritmos-y-estructuras-de-dat… Revisado el 11/05/2022.
Complementaria:
Condor y De la Cruz. Algoritmos resueltos con Python. Eidec editorial, 2020. ISBN: 978-958-53018-2-5. https://doi.org/10.34893/6kbn-5a63
- CB2] That students know how to apply their knowledge to their work or vocation in a professional manner and possess the skills that are usually demonstrated through the development and defense of arguments and problem solving within their area of study.
- CB4] Students should be able to transmit information, ideas, problems and solutions to both specialized and non-specialized audiences.
- CB5] That students have developed the learning skills necessary to undertake further studies with a high degree of autonomy.
- CG1] Ability to conceive, write, organize, plan, and develop models, applications and services in the field of artificial intelligence, identifying objectives, priorities, deadlines, resources and risks, and controlling the established processes.
- CG2] Ability to solve problems with initiative, decision making, autonomy and creativity.
- CG3] Ability to design and create quality models and solutions based on Artificial Intelligence that are efficient, robust, transparent and responsible.
- CG4] Ability to select and justify the appropriate methods and techniques to solve a specific problem, or to develop and propose new methods based on artificial intelligence.
[CE2] Ability to solve artificial intelligence problems that require algorithms, correctly applying software development and user-centered design methodologies.
- CE3] Ability to understand and master the basic concepts of logic, grammars and formal languages to analyze and improve solutions based on artificial intelligence.
- TR2] Ability to work in a team, in interdisciplinary environments and managing.
- TR3] Ability to create new models and solutions in an autonomous and creative way, adapting to new situations. Initiative and entrepreneurial spirit.
The following teaching methodologies will be used: Expository Sessions (ES) and Interactive Sessions (IS). The ES will be lectures in which theoretical concepts will be taught, exercises and problems will be solved. The IS will be practical sessions in a computer classroom.
It will include:
Completion of problems, practicals, projects and/or delivery of reports with a weighting of 30% of the final grade.
Passing of partial and/or final tests, with a weighting of 70% of the final grade. It will be necessary to achieve a 5 in the partial/final tests to pass the subject. If the student does not pass the tests, the final grade will be the grade of the continuous evaluation.
The grade will be not presented when both no homework of the continuous evaluation and no partial or final test are handed in.
The evaluation criteria for the theory and practical parts in the recovery opportunity will be exactly the same as for the common opportunity. In order to pass the continuous evaluation of the subject it will be necessary to pass all the proposed activities as they are proposed throughout the course.
Lectures (theoretical, exercises or problems): 20 hours, 100% face-to-face.
Practical sessions in a computer classroom and/or laboratory: 30 hours, 100% attendance
Personal work of the students (study, exercises, practices, projects) and other activities (evaluation): 99 hours, 0% face-to-face.
Recommended Prerequisites: Programming I, Discrete Mathematics
María Jesús Taboada Iglesias
Coordinador/a- Department
- Electronics and Computing
- Area
- Computer Science and Artificial Intelligence
- Phone
- 881813561
- maria.taboada [at] usc.es
- Category
- Professor: University Professor
David Chaves Fraga
- Department
- Electronics and Computing
- Area
- Computer Science and Artificial Intelligence
- Phone
- 881815525
- david.chaves [at] usc.es
- Category
- Professor: LOU (Organic Law for Universities) PhD Assistant Professor
| Tuesday | |||
|---|---|---|---|
| 12:00-14:30 | Grupo /CLIL_03 | Spanish | IA.12 |
| Wednesday | |||
| 11:00-12:00 | Grupo /CLE_01 | Spanish | IA.11 |
| 12:00-14:30 | Grupo /CLIL_02 | Spanish | IA.12 |
| Friday | |||
| 10:00-12:30 | Grupo /CLIL_01 | Spanish | IA.12 |
| 13:30-14:30 | Grupo /CLE_01 | Spanish | IA.11 |
| 05.27.2025 09:00-14:00 | Grupo /CLE_01 | IA.01 |
| 05.27.2025 09:00-14:00 | Grupo /CLIL_02 | IA.01 |
| 05.27.2025 09:00-14:00 | Grupo /CLIL_03 | IA.01 |
| 05.27.2025 09:00-14:00 | Grupo /CLIL_01 | IA.01 |
| 05.27.2025 09:00-14:00 | Grupo /CLIL_01 | IA.11 |
| 05.27.2025 09:00-14:00 | Grupo /CLE_01 | IA.11 |
| 05.27.2025 09:00-14:00 | Grupo /CLIL_02 | IA.11 |
| 05.27.2025 09:00-14:00 | Grupo /CLIL_03 | IA.11 |
| 05.27.2025 09:00-14:00 | Grupo /CLIL_02 | IA.12 |
| 05.27.2025 09:00-14:00 | Grupo /CLIL_03 | IA.12 |
| 05.27.2025 09:00-14:00 | Grupo /CLE_01 | IA.12 |
| 05.27.2025 09:00-14:00 | Grupo /CLIL_01 | IA.12 |
| 07.09.2025 09:00-14:00 | Grupo /CLIL_03 | IA.11 |
| 07.09.2025 09:00-14:00 | Grupo /CLE_01 | IA.11 |
| 07.09.2025 09:00-14:00 | Grupo /CLIL_01 | IA.11 |
| 07.09.2025 09:00-14:00 | Grupo /CLIL_02 | IA.11 |