To operate the Blended Learning Center(BLC) at optimal level, maintenance will be performed every day at 8:30 AM and at 5:00 PM regularly which can take up to 30 minutes. Please consider scheduling your activity in the BLC platform accordingly.
Enrolment options
Course
Rationale
An introduction to data mining; Data preparation, model building, and
data mining techniques such as clustering, decisions trees and neural networks;
Induction of predictive models from data: classification, regression, and
probability estimation; Application case studies; Data-mining software tools
review and comparison.
Course Objectives
- To
appreciate the necessity of data mining in everyday life
- To
apply the concept of data mining in solving problems
- To
demonstrate applications of data mining using tools
- To
apply knowledge of data mining in project work
- CO1 Able to grasp the basic Data Mining Principles
- CO2 Able to identify appropriate data mining algorithms to solve real world problems
- CO3 Able to compare and evaluate different data mining techniques like classification, prediction, clustering and association rule mining
- CO4 Able to apply data mining knowledge in problem solving