Advanced Certificate in Data Analytics in Digital Economy Module 3: Statistical Analysis and Machine Learning for Business Insights

Analytics & Tech
Innovation & Business Improvement

Next Intake: 20 Apr 2026 (Mon)

Basic
SkillsFuture
Short Courses
This module is part of Advanced Certificate in Data Analytics in Digital Economy

This module is conducted in-person.

Next course starts on

20 Apr 2026 (Mon) See Full Schedule

Fee

SGD2,180* (as low as SGD254 after maximum funding) Learn More

Duration

2 Full Days (Weekdays)

Level

Basic

Who Should Attend

Data analysts, data scientists, business analysts, marketing analysts, financial analysts, and professionals involved in strategic decision-making within organizations.

PREREQUISITES

There are no prerequisites for this programme. Prior knowledge on any of the topics is not required

Overview

Module 3 is designed to equip participants with the knowledge and skills necessary to leverage statistical analysis and machine learning techniques in a business context. The module will cover foundational statistical concepts, exploratory data analysis, hypothesis testing, regression analysis, classification models, clustering techniques, and time series analysis. Participants will also learn how to apply these methods to extract valuable insights from large datasets, make data-driven decisions, identify patterns and trends in business data, predict future outcomes, optimise processes, and drive strategic decision-making. Emphasis will be placed on practical applications of statistical analysis and machine learning algorithms using popular tools such as Python or R. By the end of this module, students will have a solid understanding of how statistical analysisand machine learning can be used to derive actionable insights that drive business performance in the digital economy.

Learning Objectives

At the end of the 2-day module, participants will be able to:

Understand the fundamental principles of statistical analysis and machine learning algorithms commonly used in business analytics
Apply statistical techniques to analyze and interpret complex business data sets, identifying patterns, trends, and correlations that can provide valuable insights for decision-making
Develop proficiency in using machine learning models to predict future business outcomes based on historical data, including regression analysis, classification algorithms, and clusteringmethods
Evaluate the ethical considerations and potential biases associated with applying statistical analysis and machine learning in a business context, ensuring responsible use of data-driveninsights
Demonstrate the ability to communicate findings from statistical analysis and machine learning models effectively to non-technical stakeholders within a business environment, facilitating informed decision-making processes

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%
+ ETSS Funding 20%)

$654

(After SSG Funding 70%)

Singapore Citizen ≥ 40 years old

$254

(After SSG Funding 70%
+ MCES Funding 20%)

$254

(After SSG Funding 70%
+ ETSS Funding 20%)

$254

(After SSG Funding 70%
+ MCES Funding 20%)

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