Singapore University of Social Sciences

Text Mining and Big Data for Decision Making (CET106)

Applications Open: To be confirmed

Applications Close: To be confirmed

Next Available Intake: To be confirmed

Course Types: Short Course, SkillsFuture Series

Language: English

Duration: 1 day

Fees: To be confirmed

Area of Interest: Business Administration

Schemes: Lifelong Learning Credit (L2C)

Funding: SkillsFuture

Venue: Singapore University of Social Sciences

We are in the midst of a data explosion that is creating unique challenges and opportunities for organizations. Unless data can help decision makers make better decisions, enhance strategic initiatives, better communicate with consumers, better allocate resources, there is little value to this resource, big or otherwise.

This course discusses the use of text mining and Big Data in decision making. Topics include text mining terminology and hierarchy, challenges in dealing with text, text mining process and applications, overview of Big Data, various Big Data analytics techniques and challenges of Big Data.


A. Knowledge and Understanding (Theory Component)

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

  • Define text mining and its process
  • Explain the hierarchy in text mining terminology
  • Outline the challenges in dealing with text
  • Define the characteristics of Big Data
  • Explain the potential benefits and challenges of using Big Data
  • State the differences between Hadoop and the traditional databases in supporting Big Data
  • List the various Big Data analytics techniques
  • Discuss the challenges of Big Data

B. Key Skills (Practical Component)

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

  • Recommend the appropriate analytics techniques to generate useful information to support decision-making for a variety of business and other problems


09:00 Course Overview
09:15Overview of Text Mining
10:45Text Mining and its Challenges
13:30 Demo on Text Mining
14:30Overview of Big Data
15:45 Big Data Analytics
17:00Assessment (MCQs)

About the Trainer

Professor Lee Yew Haur is currently Head of Programme for Business Analytics at the Singapore University of Social Sciences. He has more than fifteen years of experience in text mining and data mining. His main research and teaching interests are in text mining, data mining and web mining. He has also published in several international journals and conferences.

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
SSG Funding without GST
Nett Course Fee after SSG funding
(A) - (B) = (C)
GST based on Nett fee
Nett Fee payable after GST
(C) + (D) = (E)
Additional Funding subjected to eligibility
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

* 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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