On successful completion of the Course students will be able to:
Course Content
1. Overview
- Brief description of data mining
- Data warehousing, data mining and database technology
- Online Transaction processing and data mining
2. Data warehousing
- Design
- Tools
- Operations
- Issues
3. Data Preprocessing
4. Classification rule Mining
- Description
- Principle
- Design
- Algorithm
- Rule evaluation
5. Clustering
- Description
- Principle
- Design
- Algorithm
6. Association rule Mining
- Description
- Principle
- Design
- Algorithm
- Rule evaluation
This course will be offered through lectures, presentations, class discussions, laboratory work and Group project work. Students present their assignments, and get feedbacks.
Method of Assessment
The detail of the evaluation criteria and their percentage share is shown below:
Final Project Description (45%):
Prepare a publishable paper that has abstract (1 page), introduction, problem statement & objective (1-2 pages), literature review (3 pages), methods (1 page) and experimentation (discuss any preprocessing, model creation, test results, findings) (2-3 pages), concluding remarks & recommendation (1 page) and References (1 page).
The Course is about discovering hidden pattern (knowledge) from a given data warehouse or data source using different data mining functionalities for research and business applications