Advanced Certificate in Data Analytics in Digital Economy Module 5: Predictive Modeling and Decision Making
- Analytics & Tech
- Innovation & Business Improvement
This module is conducted in-person.
2 Full Days (Weekdays)
Who Should Attend
- Data analysts, business intelligence professionals, data scientists, professionals working in fields relating to finance, marketing, healthcare, and ecommerce
PREREQUISITES
There are no prerequisites for this programme. Prior knowledge on any of the topics is not required
Overview
Module 5 provides participants with a comprehensive understanding of how predictive modeling techniques can be applied to make informed decisions in the digital economy. The module covers advanced statistical methods, machine learning algorithms, and data mining techniques that are essential for predicting future trends and outcomes.
Learning Objectives
At the end of the 2-day module, participants will be able to:
- Understand the principles and techniques of predictive modeling in the context of digital economy, including regression analysis, time series forecasting, and machine learning algorithms
- Apply statistical and computational methods to analyze large datasets from digital economy sources in order to make informed decisions using predictive modeling
- Evaluate the ethical implications and potential biases associated with predictive modeling in digital economy decision making, and develop strategies to mitigate these issues
- Utilise data visualization tools and techniques to effectively communicate insights derived from predictive models for decision making within the digital economy landscape
- Critically assess real-world case studies where predictive modeling has been used to drive strategic decision making in various sectors of the digital economy, identifying best practicesand areas for improvement
Assessment
As part of the requirement for SkillsFuture Singapore, there will be an assessment conducted at the end of the course. The mode of assessment, which is up to the trainer’s discretion, may be an online quiz, a presentation or based on classroom exercises.
Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion issued by Singapore Management University.
Calculate Programme Fee
Fee Table
COMPANY-SPONSORED | |||
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$654 (After SSG Funding 70%) |
$254 (After SSG Funding 70% |
$654 (After SSG Funding 70%) |
Singapore Citizen ≥ 40 years old |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
International Participant |
$2,180 (No Funding) |
$2,180 (No Funding) |
$2,180 (No Funding) |
All prices include 9% GST
Please note that the programme fees are subject to change without prior notice.
Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.
Self Sponsored
SkillsFuture Credit
Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.
This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.
Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).Workfare Skills Support Scheme
From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.
Company Sponsored
Enhanced Training Support for SMEs (ETSS)
- Organisation must be registered or incorporated in Singapore
- Employment size of not more than 200 or with annual sales turnover of not more than $100 million
- Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
- Trainees must be Singapore Citizens or Singapore Permanent Residents
- Trainees must not be a full-time national serviceman
- Trainees are eligible for ETSS funding only if their company's SME status is approved prior to the course commencement date. To verify your SME's status, please click here.
Please click here for more information on ETSS.
Absentee Payroll
Companies who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:
AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)
Intake Information
This module is conducted in-person.
Course | Dates |
---|---|
INTAKE 1 | 15 - 16 Jun 2026 [Open for Registration] |
*Online registration will close 5 calendar days before the course start date