Dates: 7 May 2025 and 6 August 2025
Level: Basic
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
Time | Agenda |
---|
09:00 | Course Overview |
09:15 | Overview of Text Mining |
10:30 | Break |
10:45 | Text Mining and its Challenges |
12:00 | Lunch |
13:30 | Demo on Text Mining |
14:30 | Overview of Big Data |
15:30 | Break |
15:45 | Big Data Analytics |
17:00 | Assessment (MCQs) |
Dr. Zhang Yimiao is currently the Deputy Head of Business Analytics Programme at the Singapore University of Social Sciences. She has been teaching different text mining and data mining courses in the Business Analytics Programme. Her main research interests are focused on text mining and data mining in social media, e-commerce, and blockchain-based applications.
Please submit the following documents to cet@suss.edu.sg:
- Coloured copy (back and front) of NRIC for Singaporeans and PRs, or "Employment"/"S" Pass for foreign applicant
- Application form
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 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 SUSS Academy via the following:
Telephone: +65 6248 0263
Email:
CET@suss.edu.sg