Three 50 minutes lectures per week (3-0-3)
Designation: Elective Course
Course Level: Undergraduate
Prerequisite(s) by Topic:
- Data preprocessing
- Data warehouse: data model, design and implementation
- Data cube: storage, indexing, design, implementation and efficient computation
- OLAP operators
- Data mining: Association, classification, clustering, and outlier detection
Review of relational databases and Conjunctive queries, Data Warehousing Concepts and OLAP, Data Warehouse Design and Development, Information and data Integration, OLAP Technology for Data Mining. Data Mining: Primitive, Languages and Application Developments.
Data Mining Concepts and Techniques, 2nd Edition. Jiawei Han and Micheline Kamber, Morgan Kaufmann Publisher, 2005.
After completion of this course, the student shall be able to:
- Understand different methods of preprocessing data.
- Design and implement a simple data warehouse.
- Design and implement simple data cubes and OLAP operations.
- Understand the main concepts of data mining.
- Data preprocessing:
- Data warehousing Model
- Data cube:
- Efficient computation