1 |
- |
Introduction and general concepts |
Lecture, Discussion, Practice |
2 |
Literature Reading |
Fields of application of data mining |
Lecture, Discussion, Practice |
3 |
Literature Reading |
Introducing ready programs in data mining- Electronic statement programs in data mining |
Lecture, Discussion, Practice |
4 |
Literature Reading |
Preparing the data for analysis (steps) |
Lecture, Discussion, Practice |
5 |
Literature Reading |
OLAP |
Lecture, Discussion, Practice |
6 |
Literature Reading |
Classification and clustering |
Lecture, Discussion, Practice |
7 |
Literature Reading |
Decision Trees |
Lecture, Discussion, Practice |
8 |
- |
MID-TERM EXAM |
- |
9 |
Literature Reading |
Statistics in data mining |
Lecture, Discussion, Practice |
10 |
Literature Reading |
Artificial intelligence in data mining |
Lecture, Discussion, Practice |
11 |
Literature Reading |
Artificial neural networks in data mining |
Lecture, Discussion, Practice |
12 |
Literature Reading |
Association rules |
Lecture, Discussion, Practice |
13 |
Literature Reading |
Other mining techniques in data mining - Web and text mining |
Lecture, Discussion, Practice |
14 |
Literature Reading |
Case Studies |
Lecture, Discussion, Practice |
15 |
Literature Reading |
Industrial applications in data mining |
Lecture, Discussion, Practice |
16 |
- |
FINAL EXAM |
- |
17 |
- |
FINAL EXAM |
- |