Modules and seminars
The modules (M) that comprise the curriculum are shown below with the subjects (A) and seminars (S) that constitute them. Additionally, links to pages giving further detailed information about the subjects, subjects and seminars are available.
Notice: Learning guides corresponding to the seminars taught in the second semester will be published within the period stipulated by the UPM normative prior to the enrollment period.
All subjects are available at Moodle (virtual classroom 
)
ACADEMIC COURSE 2021/22
M1. Fundamentals of Research
- S1: Research methodology (description, learning guide)
- S2: Project management and risk control (description, learning guide)
- S3: Legal and ethical aspects of Artificial Intelligence (description, learning guide)
- S4: Artificial Intelligence and Inclusion (description, learning guide)
M2. Decision Analysis
- A1: Decision support systems (description, learning guide)
- A2: Participatory decision making and negotiation (description, learning guide) (Available documentation is in English but classes will be taugth in Spanish and the evaluation process will be performed in Spanish)
- A3: Simulation methods (description, learning guide)
- S5: Decision analysis (description, learning guide)
M3. Machine Learning
- A4: Bayesian networks (description, learning guide) (Available documentation is in English but classes will be taugth in Spanish and the evaluation process will be performed in Spanish)
- A5: Machine learning (description, learning guide) (Available documentation is in English but classes will be taugth in Spanish and the evaluation process will be performed in Spanish)
- A6: Artificial neural networks and Deep learning (description, learning guide) (Available documentation is in English but classes will be taugth in Spanish and the evaluation process will be performed in Spanish)
- A20: Explainable artificial intelligence (NEW in 2023-24)
- S6: Machine learning (description, learning guide)
M4. Natural Computing
- A7: Metaheuristic-based intelligent search (description, learning guide)
- A8: Evolutionary computation (description, learning guide)
- A9: Programmable biology: DNA computing and biocircuits engineering (description, learning guide)
- S7: Natural computing (description, learning guide)
M5. Knowledge Representation and Reasoning
- A10: Logic programming (description, learning guide)
- A11: Multi-agent systems (description, learning guide) (Available documentation is in English but classes will be taugth in Spanish and the evaluation process will be performed in Spanish)
- A12: Ontological engineering (description, learning guide)
- A13: Models of reasoning (description, learning guide) (Available documentation is in English but classes will be taugth in Spanish and the evaluation process will be performed in Spanish)
- S8: Knowledge representation and reasoning (description, learning guide)
- S9: Fuzzy logic (description, learning guide)
- S10: Cognitive computing (description, learning guide)
M6. Cognitive Robotics and Perception
- A14: Computer vision (description, learning guide)
- A15: Autonomous robots (description, learning guide)
- S11: Cognitive robotics and perception (description, learning guide)
- S12: Principals of robotics locomotion (description, learning guide)
M7. Application Areas
- A16: Biomedical informatics (description, learning guide)
- A17: Language engineering (description, learning guide)
- A18: Web science (description, learning guide) (Available documentation is in English but classes will be taugth in Spanish and the evaluation process will be performed in Spanish)
- A19: Deep Learning for Natural Language Processing (description, learning guide)
- S13: Applications of Artificial Intelligence (description, learning guide)
- S14: Natural language processing (description, learning guide)
- S15: Automated planning (description, learning guide)
M8. Seminars by visiting professors
: Offered in english
English