Singapore University of Social Sciences

Data Mining for Decision Making

Applications Open: To be confirmed

Applications Close: To be confirmed

Next Available Intake: To be confirmed

Schemes: Lifelong Learning Credit (L2C)

Language: English

Duration: 1 day

Fees: To be confirmed

Area of Interest: To be confirmed


Venue: Singapore University of Social Sciences

Data mining is a very important tool that has helped to create new ideas and critical decision making in organisations, enterprises and government institutions. Data mining tools and techniques provide the right information for leaders so that the decisions taken might become positive realities. So how is data mining applied to strategic decision making?

This course provides an overview of data mining methodology and techniques, concepts and applications of association analysis, clustering and predictive modelling, and also presents the challenges and limitations of data mining.

Objective

A. Knowledge and Understanding (Theory Component)

By the end of this course, participants should be able to:

  • Differentiate the various aspects of data mining
  • Recommend data mining tools for association analysis, clustering and predictive modelling
  • Discuss the use of data mining to support decision making

B. Key Skills (Practical Component)

By the end of this course, participants should be able to:

  • Plan the process of data mining, i.e. CRISP-DM framework
  • Execute techniques such as association analysis with Apriori, clustering with K-means, and classification with CHAID (Chi-Square Automatic Interaction Detection)
  • Justify the use of appropriate data mining techniques for different business problems
  • Interpret the results of a data mining analysis
  • Evaluate the performance of data mining models
  • Apply data mining using a software package, interpret the output, and recommend solutions for the problem(s) under consideration

Topics

TimeAgenda
09:00 Course Overview
09:15Fundamental of Data Mining
10:30Break
10:45Association and Clustering
12:00Lunch
13:30 Hands-on with IBM SPSS Modeler
14:30Predictive Modelling I
15:30Break
15:45 Predictive Modelling II
17:00Assessment (MCQs)


Requirements

NIL

About the Trainer

Professor Koh Hian Chye is currently Director of the Business Intelligence & Analytics Unit at the Singapore University of Social Sciences. His main research and teaching interests are in data mining, business analytics and learning analytics. He has published widely in international journals and conferences, and has served as a statistical and data mining consultant to several organisations.

Application Procedures

Please submit the following documents to Y2V0QHN1c3MuZWR1LnNn:

  1. Coloured copy (back and front) of NRIC for Singaporeans and PRs, or "Employment"/"S" Pass for foreign applicant
  2. Recent payslip or income statement (For WTS scheme only)
  3. Application form

Course Fee

CategoriesFull Course Fee without GST
(A)
SSG Funding without GST
(B)
Nett Course Fee after SSG funding
(A) - (B) = (C)
GST based on Nett fee
(D)
Nett Fee payable after GST
(C) + (D) = (E)
Additional Funding subjected to eligibility
(F)
Final payable nett amount
(E) - (F) = (G)
Singapore Citizens*All aged 35 and above and earning $2000 or less per month1 $650.00$455.00$195.00 $13.65 $208.65$162.50$46.15
Sponsored by SME2$130.00$78.65
Self-Sponsored or sponsored by Non-SME aged 40 and above3$130.00$78.65
Self-Sponsored or sponsored by Non-SME aged from 21 to 39NA$208.65
PRs*Self-Sponsored or sponsored by Non-SME aged 21 and above$208.65
Sponsored by SME2$130.00$78.65
OthersNA$650.00$45.50$695.50NA$695.50

* Participants are required to achieve at least 75% attendance and/or sit and pass any prescribed examinations/assessments or submit any course/project work (if any) under the course requirement.

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