Educational guide
IDENTIFYING DATA 2024_25
Subject DATA MINING Code 00717022
Study programme
0717 - GRADO INGENIERÍA DATOS INTELIGENCIA ARTIFICIAL
Descriptors Credit. Type Year Period
6 Compulsory Third First
Language
Castellano
Prerequisites
Department ING.MECANICA,INFORMAT.AEROESP.
Coordinador
ALIJA PÉREZ , JOSÉ MANUEL
E-mail jmalip@unileon.es
raferd@unileon.es
Lecturers
ALIJA PÉREZ , JOSÉ MANUEL
FERNÁNDEZ DÍAZ , RAMÓN ÁNGEL
Web http://
General description Advanced information systems
Tribunales de Revisión
Tribunal titular
Cargo Departamento Profesor
Presidente ING.MECANICA,INFORMAT.AEROESP. CASTEJON LIMAS , MANUEL
Secretario ING.MECANICA,INFORMAT.AEROESP. MEDINA MARTINEZ , GABRIEL
Vocal ING.MECANICA,INFORMAT.AEROESP. RODRIGUEZ LERA , FRANCISCO JAVIER
Tribunal suplente
Cargo Departamento Profesor
Presidente FERNANDEZ ROBLES , LAURA
Secretario ING.MECANICA,INFORMAT.AEROESP. RODRIGUEZ DE SOTO , ADOLFO
Vocal ING.MECANICA,INFORMAT.AEROESP. PANIZO ALONSO , LUIS

Competencias
Code  
A18971
B5801
B5802
B5805
B5807
B5810
C3 CMECES3 That students have the ability to gather and interpret relevant data (normally within their area of study) to make judgments that include reflection on relevant issues of a social, scientific or ethical nature.
C4 CMECES4 That students can transmit information, ideas, problems and solutions to both a specialised and non-specialised audience

Learning aims
Competences
A18971
B5805
B5807
B5802
C4
C3
B5810
B5802
B5801
B5807

Contents
Topic Sub-topic
Block I: DATAWAREHOUSE. DATA COLLECTION PROCESS COLLECTION, CLEANING, EXPLORATION, AND SELECTION.
Block II: ADVANCED DATA MINING TECHNIQUES METRICS, VALIDATION, AND TRAINING.
Block III DESCRIPTIVE DATA ANALYSIS PREDICTIVE ANALYSIS AND CLASSIFICATION MODELS
Block IV: COMPLEX DATA MINING APPLIED:
KNOWLEDGE ADMINISTRATION.
IMPROVEMENT IN DECISION MAKING.
WEB MINING
TEXT MINING

Planning
Methodologies  ::  Tests
  Class hours Hours outside the classroom Total hours
Problem solving, classroom exercises 20 35 55
 
Personal tuition 3 0 3
 
Lecture 32 30 62
 
Extended-answer tests 5 25 30
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies   ::  
  Description
Problem solving, classroom exercises Formulation, analysis, resolution and debate of a problem or exercise, related to the subject of the subject.
Personal tuition Meeting of the teacher with a small group of students, conceptually relying on learning theories rather than teaching ones.
Lecture Exhibition of the contents of the subject.

Personalized attention
 
Personal tuition
Description
Students' doubts will be resolved in the office in a personalized way or through institutional email.

Assessment
  Description Qualification
Problem solving, classroom exercises Completion and delivery of the practical exercises carried out in the laboratory classes.
An exam will be carried out that will evaluate the knowledge acquired in the practices. 		40% Minimum grade to pass the subject: 5
Extended-answer tests Problem resolution.
They will consist of written tests for solving cases and problems. 		40% Minimum grade to pass the subject: 5
Others Delivery of optional work, attendance and participation of the student both in class and in Moodle. 20% This mark will be added when the theoretical and practical part has been passed
 
Other comments and second call
SECOND CALL:

In this case, the student must pass a final exam of all the learning results of the subject. Must obtain a minimum of five points both in the theoretical part and in the practical part.

Both the assignments and practices submitted by students can be reviewed with an anti-plagiarism program that can perform checks among the works of students from the current call, previous calls, and other external sources. In the event that plagiarism is detected, the immediate withdrawal of the exam, expulsion of the student, and grading of the work or practice as failed will proceed. In any case, the internal regulations of ULE included in the document "Guidelines for action in cases of plagiarism, copying, or fraud in exams or assessment tests" (Approved by the Permanent Commission of the Governing Council on 01/29/2015) will be adhered to.

Sources of information
Access to Recommended Bibliography in the Catalog ULE

Basic Pascual Montañes y Eduardo Olier, Corporate Governance Intelligence, Prentice Hall, Last edition
Robert Groth, Data Mining, Prentice Hall, Last edition
José Hernández Orallo, M.ª José Ramírez Quintana, César Ferri Ramírez, Introducción a la Minería de Datos, Prentice Hall, Last edition
Jordi Conesa Caralt y Josep Curto Díaz, Introducción al Business Intelligence, Editorial UOC, Last edition

Complementary


Recommendations


Subjects that it is recommended to have taken before
SIST. DE INFORMAC.ASPECTOS LEGALES Y ÉTI / 00717004
PROGRAMACIÓN / 00717005
MACHINE LEARNING / 00717014
DATABASES / 00717015
SOFTWARE ENGINEERING / 00717020