1. Cognitive domain:
Understanding: Explaining ideas or concepts Databases and Mining.
Application: Application of database and Mining concepts.
Analysis: Analyze database and Mining concepts into their component parts.
Creation: Synthetic work in Databases and Mining
2. Emotional domain:
Response: Active participation of learners with the presentation of a synthetic assignement on data bases and Mining
Valueing: Critical assessment of research articles in Database and Mining research field
3. Psychomotor domain:
Manipulation: Ability to perform specific actions on an data base and Mining management system (MS SQL Server).
Level 6: The student will have advanced knowledge in databases and Mining , involving a critical understanding of theories and principles.
Level 6: The student will possess advanced skills in a database and Mining management system and will be able to prove it by using a DBMS.
Level 5: The student will be able to manage and oversee the creation of a database and Mining process.
Course Content (Syllabus)
Data base Architecture, Modeling data with entity-relationship model, Relational model and relational algebra, language SQL, Relational calculus, database design, and multivalued Functional Dependencies, Normal forms. Languages and architectures for data mining, association rules, Classification and prediction, Glustering, Mining complex data types (text, time series, spatial data, DNA, Wed data etc).
Additional bibliography for study
. Συστήματα Βάσεων Δεδομένων: Θεωρία και Πρακτική Εφαρμογή, Ιωάννης Μανωλόπουλος και Απόστολος Παπαδόπουλος, Εκδόσεις Νέων Τεχνολογιών.
. Dunham M.: “Data Mining: Introductory and Advanced Topics”, Prentice Hall, 2003
. Han J. and Kamber M.: “Data Mining: Concepts and Techniques”, Morgan Kaufmann, 2001
. Chakrabarti S.: “Mining the Web”, Morgan Kaufmann, 2003