Singapore University of Social Sciences

Data Mining for Decision Making

Data Mining for Decision Making (CET105)

Applications Open: 15 October 2020

Applications Close: 22 January 2021

Next Available Intake: 05 February 2021

Course Types: Short Course, SkillsFuture Series

Language: English

Duration: 1 day

Fees: $650

Area of Interest: Business Administration

Schemes: Lifelong Learning Credit (L2C)

Funding: SkillsFuture

School/Department: Centre for Continuing & Professional Education


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 cet@suss.edu.sg:

  1. Coloured copy (back and front) of NRIC for Singaporeans and PRs, or "Employment"/"S" Pass for foreign applicant
  2. Application form

Course Fee

International ParticipantsS'poreans (aged below 40) and PRsSkillsFuture Mid-Career Enhanced Subsidy1
(S'poreans aged 40 and above)
Enhanced Training Support for SMEs2
Full Course fee (A)$650$650$650$650
SSG grant (70%) (B)-($455)($455)($455)
Nett course fee (A) - (B) = (C)$650$195$195$195
7% GST on nett course fee (D)$45.50$13.65$13.65$13.65
Total nett course fee payable, including GST (C) + (D) = (E)$695.50$208.65$208.65$208.65
Less additional funding if eligible under various schemes (F)--($130)($130)
Total nett course fee payable, including GST, after additional funding from the various funding schemes (E) - (F) = (G)$695.50$208.65$78.65$78.65

1 Mid-Career Enhanced Subsidy: Singaporeans aged 40 and above may enjoy subsidies up to 90% of the course fees.
2 Enhanced Training Support for SMEs: SME-sponsored employees (Singaporean Citizens and PRs) aged 21 and above may enjoy subsidies up to 90% of the course fees.

  • 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.
  • Participants are required to complete all surveys and feedbacks related to the course.
  • The course fees are reviewed annually and may be revised. The University reserves the right to adjust the course fees without prior notice.
  • Singapore University of Social Sciences reserves the right to amend and/or revise the above schedule without prior notice.

For clarification, please contact the Centre for Continuing and Professional Education (CCPE) via the following:

Telephone: +65 6248 0263
Email: CET@suss.edu.sg
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