DATAWAREHOUSES AND DATA MINING

Course Information
TitleΑΠΟΘΗΚΕΣ ΔΕΔΟΜΕΝΩΝ ΚΑΙ ΕΞΟΡΥΞΗ ΔΕΔΟΜΕΝΩΝ / DATAWAREHOUSES AND DATA MINING
CodeNIS-07-03
FacultySciences
SchoolInformatics
Cycle / Level1st / Undergraduate
Teaching PeriodWinter
CoordinatorAnastasios Gounaris
CommonNo
StatusActive
Course ID40002983

Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)

Registered students: 1
OrientationAttendance TypeSemesterYearECTS
GENIKĪ KATEUTHYNSĪYPOCΗREŌTIKO KATA EPILOGĪ745

Class Information
Academic Year2018 – 2019
Class PeriodWinter
Faculty Instructors
Weekly Hours4
Class ID
600121243
Type of the Course
  • Scientific Area
Course Category
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Examination)
Learning Outcomes
Training on methodologies for knowledge discovery in databases. Understanding of the main methodologies for classification, clustering, and association rules. Deeper study of database technologies and familiarization with data warehouses. Acquisition of skills in applying data warehouse and data mining techniques, and in using existing tools. Acquisition of skills in extractging knowledge from data and evaluating the results.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Introduction, data issues and data preprocessing, data warehouses, classification, clustering, association rules, outlier detection, applications and case studies, practical exercises in MatLab/SQLServer.
Keywords
Data Warehouses, Data Processing, Classification, Clustering, Association Rules
Educational Material Types
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures48
Laboratory Work4
Project50
Written assigments48
Total150
Student Assessment
Description
Written exams, and projects. The exact procedure and weightning is announced on the course's website.
Student Assessment methods
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Performance / Staging (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
"Εισαγωγή στην Εξόρυξη και τις Αποθήκες Δεδομένων" (Α.Νανόπουλος, Ι. Μανωλόπουλος).
Additional bibliography for study
- Margaret Dunham, Data Mining Introductory and Advanced Topics, ISBN: 0130888923, Prentice Hall, 2003 - Jiawei Han, Micheline Kamber, Data Mining : Concepts and Techniques, 3rd edition, Morgan Kaufmann, ISBN 978-0123814791, 2011 - Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining, Pearson Addison Wesley, 2006 - Mehmed Kantardzic, Data Mining: Concepts, Models, Methods, and Algorithms, ISBN: 0471228524, Wiley-IEEE Press, 2002.
Last Update
08-06-2016