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


Course Objective

  • 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


Skill Level: Beginner
Self enrolment (Student)