Description

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

Objectives

On successful completion of the Course students will be able to:

 

Course Content

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

Methodology

This course will be offered through lectures, presentations, class discussions, laboratory work and Group project work. Students present their assignments, and get feedbacks.

Assessment

Method of Assessment

 

The detail of the evaluation criteria and their percentage share is shown below:

 

  1. Researching data warehouse architecture (individual work): 5%
  2. Critical review of data mining and data warehouse paper (group work) and make presentation: 20%
  3. Write a report (concept note) on selected topics (group work) and make presentation: 20%
  4. Online Oral Examination (Questions with lottery based): 10%
  5. Final Project Work (Individual): 45%

 

 

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).

References