ECTS credits ECTS credits: 6
ECTS Hours Rules/Memories Student's work ECTS: 99 Hours of tutorials: 1 Expository Class: 15 Interactive Classroom: 35 Total: 150
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: First Semester
Teaching: With teaching
Enrolment: Enrollable
Obtain basic knowledge about Artificial Intelligence: its evolution, types of problems it deals with and techniques to solve them, social, economic, ethical and employment impacts...
Theoretical classes:
T1: Historical perspective of AI
AI Problem Solving Strategies
T2: State space search
T3: Knowledge-based
T4: Connectionist systems
Automatic learning
T5: Linear and logistic regression
T6: Supervised learning
T7: Unsupervised learning
T8: Repercussions of AI: socio-economic, ethical...
Interactive classes:
CI1: Interactive seminars on various applications, both in operation and in research
CI2: Oral Communication Seminar
CI3: Discussions on topics related to the social, economic, ethical... impact of AI.
Writing competition on current issues in AI -optional-.
Labs:
P1: Searching in state spaces
P2: Knowledge-based systems
P3: Machine Learning
Bibliography of special interest:
1. J. Palma, R. Marín (eds.). Inteligencia Artificial. Métodos, técnicas y aplicaciones. McGrawHill. (2008). ISBN: 9788448156183
2. Fernández Galán, S., González Boticario, J., Mira Mira, J. Problemas Resueltos de Inteligencia Artificial Aplicada. Búsqueda y Representación. Addison Wesley. (1998). ISBN: 9788478290178
3. Russell, S., Norvig, P. Artificial Intelligence (A Modern Approach), (4th Edition Global Edition, 2022). ISBN: 9781292401133.
4. Nilsson, N.J. Inteligencia artificial (Una nueva síntesis). McGraw-Hill. (2001). ISBN: 9788448128241
5. Gendreau, Michel, Potvin, Jean-Yves. Handbook of Metaheuristics. Springer-Verlag. (2010). ISBN: 978-1-4419-1665-5
6. Ian Goodfellow, Yoshua Bengio and Aaron Courville, “Deep Learning”, An MIT Press book, 2016
7. Simon O. Haykin, "Neural Networks and Learning Machines", Prentice Hall, 3rd edition, 2008. ISBN 0131471392
Contribute to achieve the competences included in the memory of the Degree in Computer Engineering of the USC (CG4, CG8, CG9, TR1-3, RI6-7, RI15, TI1), especially:
BASIC AND GENERAL
CG4- Ability to define, evaluate and select hardware and software platforms for the development and implementation of systems,
services and computer applications, in accordance with the knowledge acquired.
CG8- Knowledge of the basic subjects and technologies, which enable the learning and development of new methods and technologies.
technologies, as well as those that provide them with a great versatility to adapt to new situations.
CG9- Ability to solve problems with initiative, decision-making, autonomy and creativity. Ability to know how to
communicate and transmit the knowledge, skills and abilities of the profession of Technical Engineer in Computer Science.
TRANSVERSAL
TR1- Instrumental: Capacity for analysis and synthesis. Capacity for organization and planning. Oral and written communication in
Galician, Spanish and English. Ability to manage information. Problem solving. Decision making.
TR3. Systemic: Autonomous learning. Adaptation to new situations. Creativity. Initiative and entrepreneurial spirit.
Motivation for quality. Sensitivity towards environmental issues
SPECIFIC
RI15- Knowledge and application of the fundamental principles and basic techniques of intelligent systems and their application.
practice
IT1 - Ability to understand an organisation's IT environment and its IT requirements
information and communications
RI6 - Knowledge and application of basic algorithmic procedures of computer technologies for designing solutions
to problems, analyzing the suitability and complexity of the proposed algorithms.
RI7 - Knowledge, design and efficient use of the most appropriate data types and data structures to solve a problem
The didactic methodology will be based on individual work -although sometimes in groups-, discussion with the teacher in class and individual tutorials.
For each topic or thematic block of the expository classes, the teacher will prepare the contents, explain the objectives of the topic to the students in class, suggest bibliography, provide them with additional work material, etc. In the expository classes the competences CG4, CG9, TR1, RI15, TI1 will be worked on. In addition, teachers will propose to students a set of activities to be carried out, individually or in groups (work, presentations, readings, practices ...) Students should generally present them to the teacher for evaluation, for which the deadlines for delivery/presentation will be indicated through the channels used for student-teacher communication. These activities will allow the development of the competences CG4, CG8, CG9, TR1-3, RI15.
The practices and part of the interactive sessions will be developed in the Computer Room of the School, using various software tools for each of the thematic blocks. The realization of the practices will allow to develop the competences CG4, CG8, TR1-3, RI6-7, RI15.
Students will work individually or in small groups, with the constant support of the teaching staff. There will be scripts of practices, seminars, and other activities to be carried out individually or in small groups.
The teaching will be supported by the USC virtual platform in the following way: repository of the documentation related to the subject (texts, presentations, recommended readings...) and virtual tutoring of students (e-mail, forums).
The learning assessment considers both the theoretical part (40%) and the practical part (50%) and the interactive activities (10%). To pass the subject an overall mark equal to or higher than 5, out of a maximum score of 10 points, must be achieved, according to the following criteria:
- Theoretical part: will be evaluated in a single exam to be held on the official date. The grade of the exam must be equal to or higher than 4 out of a maximum score of 10 points to pass the whole subject. Otherwise, it will have to be repeated in the recovery opportunity.
- Practical part: evaluation of all the practical activities proposed by the teachers (delivery of papers, presentations in the classroom, delivery of exercises, practical work...). All the practical activities will have the same weight in the practical grade. The grade for this part must be equal or higher than 4 out of a maximum score of 10 points to pass the whole subject. Those labs with a grade lower than 3 points must be evaluated in the second opportunity.
- Interactive activities: evaluation of all the compulsory interactive activities proposed by the teacher (delivery of work, presentations and participation in the classroom, delivery of exercises ... The compulsory interactive activities will be assessed globally on a maximum of 10 points and the points awarded for the completion of voluntary activities may be added to the result, having in any case 10 as the maximum final score for this part. The grade for this part must be equal to or higher than 4 out of a maximum of 10 points to pass the subject. If this is not the case, this part will have to be evaluated in the recovery opportunity in case of not having obtained a grade of at least 3 points in it.
The final grade of the subject will be the arithmetic average weighted by the percentages indicated above of the theoretical and practical parts and complementary activities. In case of incurring in any of the situations indicated above for not reaching in one or more parts the minimum grade required to pass the subject globally, the final grade of the opportunity will be the minimum of the grades obtained in those parts.
Students who have not taken the exam and have not submitted to the evaluation of any other compulsory activity will obtain the grade of not presented.
To pass the course in July, students must undergo the evaluation of all those compulsory parts pending, as specified above. For the rest, the grades obtained during the course will be retained.
In the case of fraudulent performance of exercises or tests, it will apply the provisions of the rules of evaluation of the academic performance of students and review of grades (https://www.xunta.gal/dog/Publicados/2011/20110721/AnuncioG2018-190711-…). In application of the regulations of the ETSE on plagiarism (approved by the Xunta da ETSE on 19/12/2019), the total or partial copy of any exercise of practices or theory will mean the failure of the two opportunities of the course, with the qualification of 0.0 in both cases (https://www.usc.es/etse/files/u1/NormativaPlagioETSE2019.pdf).
Classroom work time: 58 total hours, divided into 15h (lectures), 35h (seminars and practicals), 3h (tutorials) and 5h (controls).
Personal work time: 92h (total), divided into 62h (autonomous study of theory and practices) and 30h (work, projects, and other activities).
We recommended students to solve, implement, verify, and validate all the proposed exercises and practices (not only the evaluable ones). It is also considered important to make an intense use of tutorials for the resolution of doubts.
The predominant language of instruction in the subject will be Galician.
Senén Barro Ameneiro
Coordinador/a- Department
- Electronics and Computing
- Area
- Computer Science and Artificial Intelligence
- Phone
- 881816469
- senen.barro [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
Nicolas Vila Blanco
- Department
- Electronics and Computing
- Area
- Computer Science and Artificial Intelligence
- nicolas.vila [at] usc.es
- Category
- Professor: LOU (Organic Law for Universities) PhD Assistant Professor
| Monday | |||
|---|---|---|---|
| 11:00-12:00 | Grupo /CLE_01 | Galician | IA.S1 |
| 15:30-18:30 | Grupo /CLIL_02 | Galician, Spanish | IA.S2 |
| Tuesday | |||
| 15:30-18:30 | Grupo /CLIL_03 | Spanish, Galician | IA.S2 |
| Wednesday | |||
| 09:00-10:00 | Grupo /CLE_01 | Galician | IA.S1 |
| 10:00-11:00 | Grupo /CLE_01 | Galician | IA.S1 |
| 17:00-20:00 | Grupo /CLIL_04 | Galician, Spanish | IA.04 |
| Friday | |||
| 15:30-18:30 | Grupo /CLIL_01 | Galician, Spanish | IA.04 |
| 01.09.2025 10:00-14:00 | Grupo /CLE_01 | IA.S1 |
| 01.09.2025 10:00-14:00 | Grupo /CLIL_01 | IA.S1 |
| 01.09.2025 10:00-14:00 | Grupo /CLIL_02 | IA.S1 |
| 01.09.2025 10:00-14:00 | Grupo /CLIL_03 | IA.S1 |
| 01.09.2025 10:00-14:00 | Grupo /CLIL_04 | IA.S1 |
| 01.09.2025 10:00-14:00 | Grupo /CLE_01 | IA.S2 |
| 01.09.2025 10:00-14:00 | Grupo /CLIL_01 | IA.S2 |
| 01.09.2025 10:00-14:00 | Grupo /CLIL_02 | IA.S2 |
| 01.09.2025 10:00-14:00 | Grupo /CLIL_03 | IA.S2 |
| 01.09.2025 10:00-14:00 | Grupo /CLIL_04 | IA.S2 |
| 06.24.2025 10:00-14:00 | Grupo /CLIL_04 | Classroom A2 |
| 06.24.2025 10:00-14:00 | Grupo /CLE_01 | Classroom A2 |
| 06.24.2025 10:00-14:00 | Grupo /CLIL_01 | Classroom A2 |
| 06.24.2025 10:00-14:00 | Grupo /CLIL_02 | Classroom A2 |
| 06.24.2025 10:00-14:00 | Grupo /CLIL_03 | Classroom A2 |