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Syllabus 2018-19 - 13312023 - Data Mining (Minería de datos)

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  • Level 1: Tutorial support sessions, materials and exams in this language
  • Level 2: Tutorial support sessions, materials, exams and seminars in this language
  • Level 3: Tutorial support sessions, materials, exams, seminars and regular lectures in this language
DEGREE: Grado en Ingeniería informática
FACULTY: SCHOOL OF ENGINEERING OF JAÉN

ACADEMIC YEAR: 2018-19
SYLLABUS
1. COURSE BASIC INFORMATION
NAME: Data Mining
CODE: 13312023 ACADEMIC YEAR: 2018-19
LANGUAGE: English LEVEL: 2
ECTS CREDITS: 6.0 YEAR: 4 SEMESTER: PC
 
2. LECTURER BASIC INFORMATION
NAME: PÉREZ CORDÓN, LUIS GONZAGA
DEPARTMENT: U118 - INFORMÁTICA
FIELD OF STUDY: 075 - CIENCIA DE LA COMPUTACIÓN E INT. ARTIFICIAL
OFFICE NO.: A3 - 240 E-MAIL: lgonzaga@ujaen.es P: 953213018
WEBSITE: http://wwwdi.ujaen.es/?q=es/lgonzaga
LANGUAGE: - LEVEL: 2
 
3. CONTENT DESCRIPTION

I. Introduction to Data Mining

1. Extracting knowledge in large databases. Data Mining. Applications.

II. Data preparation

2. Data collection and data preparation

3. Reduction of dimensionality

4. Discretization

III. Predictive Data Mining

5. The classification problem

6. Classification trees and rules

6. Classification with other techniques

7. Numerical prediction or regression


IV . Descriptive Data Mining

9. A ssociation rules

10. Subgroup discovery

VII. Evaluation, dissemination and use of models. Data analysis tools.

11. Evaluation , dissemination and use of models.

12. Data analysis tools .

VII. New Trends in Data Mining

13. Business Intelligence and Big Data

4. COURSE DESCRIPTION AND TEACHING METHODOLOGY

The course is divided into two related parts, theory and practice.

The theory will be conducted primarily through master classes, including activity sessions to evaluate thestudent's participation in the course.

The practical part will be held in the computer lab.

During the academic year objective tests will be performed to assess the knowledge acquired by the student

Students with special educational needs should contact the Student Attention Service (Servicio de Atención y Ayudas al Estudiante) in order to receive the appropriate academic support

5. ASSESSMENT METHODOLOGY

According to article 13 of the Regulation of Academic Regime and Evaluation of the students of the University of Jaén, the evaluation will be global.

To pass the course it will needed to pass both the theoretical and the practical part .

The theoretical part and participation will be evaluated with objective tests of theoretical concepts and practical exercises related to the subject .

The practical part of the delivery will be assessed through practical work performed by computer , with the the work relating to seminars and presentations raised and with the report associated with them . Theassessment will be continuous and incremental to evaluate both the defense end of each work and the evolution of the student during practices .

The exercises, homeworks, or cases, will be assessed through tasks, cases or exercisses proposed in class.


The portion corresponding to participation will be evaluated by some quizzes conducted during class hours corresponding to theory and practices.

6. BOOKLIST
MAIN BOOKLIST:
  • Practical applications of data mining [Recurso electrónico]. Edition: -. Author: Suh, Sang C. Publisher: Sudbury, Mass. : Jones & Bartlett Learning, c2012  (Library)
  • Data mining : concepts and techniques. Edition: 3rd ed. Author: Han, Jiawei. Publisher: Burlington, MA : Elsevier, c2012  (Library)
  • Data mining: practical machine learning tools and techniques. Edition: 3rd ed.. Author: Witten, Ian H.. Publisher: Amsterdam: Morgan Kaufman: Elsevier, 2011  (Library)
  • Data mining [Recurso electrónico] : practical machine learning tools and techniques. Edition: 3rd ed. Author: Witten, I. H. (Ian H.). Publisher: Burlington, MA : Morgan Kaufmann Publishers, 2011  (Library)
ADDITIONAL BOOKLIST:
  • Data mining techniques for marketing, sales and customer relationship management. Edition: 3rd ed.. Author: Linoff, Gordon S. Publisher: New York, NY [etc.] : Wiley, 2011  (Library)
  • Data preparation for data minig. Edition: -. Author: Pyle, Dorian. Publisher: San Francisco: Morman Kaufmann, 1999  (Library)
  • Predictive data mining : a practical guide. Edition: -. Author: Weiss, Sholom M.. Publisher: San Francisco: Morgan Kaufmann Publishers, cop. 1998  (Library)