Educational guide
IDENTIFYING DATA							2024_25
Subject	INTELLIGENT AND KNOWLEDGE-BASED SYSTEMS.					Code	00715001
Study programme	0715 - MASTER UNIV. INGENIERIA INFORMATICA
Descriptors	Credit.	Type	Year	Period
	7.5	Compulsory	First	First
Language	Castellano
Prerequisites
Department	ING.ELECTR.DE SIST. Y AUTOMATI
Coordinador	GARCÍA RODRÍGUEZ , ISAÍAS				E-mail	igarr@unileon.es arods@unileon.es mgaro@unileon.es
Lecturers	GARCÍA RODRÍGUEZ , ISAÍAS RODRÍGUEZ DE SOTO , ADOLFO GARCIA ORDAS , MARIA TERESA
Web	http://agora.unileon.es
General description
Tribunales de Revisión	Tribunal titular Cargo Departamento Profesor Presidente ING.ELECTR.DE SIST. Y AUTOMATI ALAIZ MORETON , HECTOR Secretario ING.ELECTR.DE SIST. Y AUTOMATI DIEZ DIEZ , ANGELA Vocal ING.ELECTR.DE SIST. Y AUTOMATI FUERTES MARTINEZ , JUAN JOSE Tribunal suplente Cargo Departamento Profesor Presidente ING.ELECTR.DE SIST. Y AUTOMATI ALAIZ RODRIGUEZ , ROCIO Secretario ING.ELECTR.DE SIST. Y AUTOMATI BLAZQUEZ QUINTANA , LUIS FELIPE Vocal ING.ELECTR.DE SIST. Y AUTOMATI FOCES MORAN , JOSE MARIA

Competencies

Type A	Code	Competences Specific
	A13231
	A13232
	A13233
	A13245
	A13259
	A13261
	A13262
Type B	Code	Competences Transversal
	B3094
	B3099
Type C	Code	Competences Nuclear
	C4
	C5

Learning aims

	Competences
			C4
		B3099	C5
	A13231
	A13232 A13262
	A13233
	A13245 A13261
	A13259	B3094

Contents

Topic	Sub-topic
Module I: INTELLIGENT SYSTEMS	Topic 1: Uncertainty in Artificial Intelligence: types and representation techniques. Topic 2: Introduction to machine learning. Supervised and unsupervised learning. Topic 3: Probabilistic machine learning techniques for regression and classification problems. Topic 4: Fuzzy systems Topic 5: Machine learning techniques applied to fuzzy systems. Topic 6: Probabilistic graphical models. Topic 7: Advanced machine learning techniques.
Module II: KNOWLEDGE-BASED SYSTEMS	Topic 1: Differences between reality, knowledge, and knowledge representation Topic 2: The construction of knowledge Topic 3: Implications of language in knowledge representation Topic 4: The problems posed by the automation of knowledge Topic 5: Advanced techniques on knowledge representation Topic 6: Reasoning Topic 7: Implications of mathematics and logic in the consistent construction of knowledge. Topic 8: New languages for the transmission of knowledge and its automation.

Planning

Methodologies  ::  Tests
	Class hours	Hours outside the classroom	Total hours
PBL (Problem Based Learning)	10	10	20
Problem solving, classroom exercises	10	20	30
Presentations / expositions	10	4.5	14.5
Practicals using information and communication technologies (ICTs) in computer rooms	20	20	40
Personal tuition	6	0	6
Debates	8	0	8
Lecture	20	40	60
Mixed tests	9	0	9
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies

Methodologies   ::  

	Description
PBL (Problem Based Learning)	Problem formulation and discussion. The student will carry out practical cases that will allow them to acquire the skills of the course.
Problem solving, classroom exercises	The teacher will pose and solve problems/exercises in the classroom that help understand the contents covered in the lectures.
Presentations / expositions	The students will give presentations on topics related to the course content.
Practicals using information and communication technologies (ICTs) in computer rooms	Practical implementation of the contents discussed in the lectures.
Personal tuition	Time reserved for addressing and resolving students' questions.
Debates	Activity where two or more groups defend opposing positions on a specific topic.
Lecture	Presentation of the course content.

Personalized attention

Personal tuition

Description

Assessment

	Description	Qualification
Practicals using information and communication technologies (ICTs) in computer rooms	The completion of laboratory practices, behavior during these sessions, and the documents presented as a result of these sessions will be evaluated.	45%
Mixed tests	The contents corresponding to the different methodologies (lectures, debates, practicals, problems, etc.) will be assessed through various mixed-type tests (short answer, multiple choice, essay, etc.) that will be distributed throughout the course.	Each test taken will have an equal weight in the calculation of the grade.45%
Others	Attendance and making the most of the work sessions will be positively valued.	10%
Other comments and second call

Sources of information

Access to Recommended Bibliography in the Catalog ULE

Basic	, , ,
Complementary

Recommendations