Machine Learning for SCA
*This is a non-WSQ module.
  • This module is also referred to as "Machine Learning for Supply Chain Analytics and Last Mile Logistics Planning".


In today’s connected world, machine learning has emerged as a key technologies for improving business operations in organisations. It extracts meaningful insights from raw business data for better decision support & making in the supply chain planning and operations management.

about this programme

This programme focuses on applying relevant machine learning techniques to extract hidden patterns from either commercial systems such as CRM, ERP or excel files containing large volume of transactions data amassed over the years. Some of the examples are listed below:

  • Sale Order
    • Hidden trend and patterns in demand
  • Sales + delivery (demand) order
    • Order fulfilment performance
  • Purchase + delivery (supply) order
    • Supplier performance
  • Purchase + delivery (supply) order + sales order 
    • Operational uncertainty

Who Should Attend

This programme is designed for organisations in the manufacturing and service sectors that have substantial amount of operational and transaction data. It aim to equip professionals with data analytics skill that can be utilized to discover insights for better planning of their supply chain activities. The programme is highly suitable for management officers/ directors and professional who works in the area of supply chain planning and management, logistics planning, sales and marketing function, production, operation or IT.

Course Outline

Course Outline

The programme adopts the Learn-Practise-Implement™ (LPI™) pedagogy. Participants will acquire knowledge through a gradual learning curve, reinforce the knowledge and skill taught by working on hands-on examples that are related to their work, and apply the knowledge acquired to solve their business problems.

Key focus areas or applications:

  • Data analytics fundamentals
  • Data visualization
  • Supervised learning
  • Unsupervised learning
  • Decision analysis
  • Supplier/customer profiling
  • Demand pattern discovery
  • Order lead-time analysis
  • Demand forecasting
  • Managing demand uncertainty

The machine learning topics covered in this course are aimed to provide insights for better decision support in the areas of demand planning, inventory planning and profile analysis of suppliers and customers.

Upon Completion of This Course


Participants will be awarded with a Certificate of Attendance (COA) by SIMTech and/or ARTC if they meet the following criteria:

  • Achieve at least 75% course attendance;
  • Take all assessments; and
  • Pass the course.

Note: Trainees will have to bear the full courses fee upon failure to meet either one of the criteria.

Pre-Requisites, Full and Nett Course Fees


  • Applicants should possess a degree in any discipline or a diploma with a minimum of 3 years of related working experience.
  • Applicants who do not have the required academic qualifications are still welcome to apply, but shortlisted candidates may be required to attend an interview for special approval.
  • Proficiency in written and spoken English.

Full Course Fee

The full course fee for this course is $5,000 before funding and prevailing GST.

Nett Course Fee

Singapore Citizens aged 39 years and below, Singapore Permanent Residents and LTVP+ Holders
Employer-sponsored and self-sponsored Singapore Citizens aged 40 yrs and above (MCES² SME-sponsored local employees (i.e Singapore Citizens, Singapore Permanent Residents and LTVP+ Holders (ETSS¹
All fees are inclusive of GST 9%.
Please note that fees and funding amount are subject to change.


  • The LTVP+ scheme applies to lawful foreign spouses of Singapore Citizens with (i) at least one Singapore Citizen child or are expecting one from the marriage, or at least three years of marriage, and (ii) where the Singapore Citizen sponsor is able to support the family.
  •  All LTVP+ holders can be identified with their green visit pass cards, with the word ‘PLUS’ printed on the back of the card.


SMEs that meet all of the following eligibility criteria:

  • Registered or incorporated in Singapore
  • Employment size of not more than 200 or with annual sales turnover of not more than $100 million

SME-sponsored Trainees:

  • Must be Singapore Citizens or Singapore Permanent Residents.
  • Courses have to be fully paid for by the employer.
  • Trainee is not a full-time national serviceman. 

Further Info: This scheme is intended for all organisations, including non-business entities not registered with ACRA e.g. VWOs, societies, etc. Only ministries, statutory boards, and other government agencies are NOT eligible under Enhanced Training Support for SMEs Scheme. Sole proprietorships which meet all of the above criteria are also eligible.


SkillsFuture Credit

For more information on the SkillsFuture funding schemes you are eligible for, please visit

How course fees are calculated

International ParticipantsSingapore Citizens aged 39 years and below, Singapore Permanent Residents and LTVP+ Holders Employer-sponsored and self-sponsored Singapore Citizens aged 40 years and above SME-sponsored local employees (i.e Singapore Citizens, Singapore Permanent Residents and LTVP+ Holders)
Not applicable for SkillsFuture FundingSkillsFuture Funding (Baseline)SkillsFuture Mid-career Enhanced Subsidy (MCES) ²SkillsFuture Enhanced Training Support for SMEs (ETSS) ¹
 Full Course Fee $5,000$5,000 $5,000 $5,000 
SkillsFuture FundingNot Applicable  ($3,500)($4,500)($4,500)
Nett Course Fee$5,000 $1,500$500$500
GST 9%
Total Nett Course Fee Payable to Training Provider $5,450 $1,635$635$635
* Based on 30% of Full Course Fee

Contact Us

  • For technical enquiries, please contact:

Ms YAN Wenjing,

  • For general enquiries, please contact:

Knowledge Transfer Office,


  • Please register for this course through our Course Registration Form for Public Classes.
  • For the first question, please select "Modular Programmes".
  • Applicants will be placed on our waiting list if the course does not have an upcoming scheduled intake.
  • Once the next intake is confirmed to commence, SIMTech will contact the applicants to share the class information.


Skills Course Reference Number  Next Intake(s)'s Training Period
(Click on the dates to view its schedules)
Registration Status 
  • Machine Learning for Supply Chain Analytics and Operations Management (40 hours)
TGS-2020503195  PM19 Aug 2024 - 21 Oct 2024

Note: SIMTech and ARTC reserve the right to change the class/schedule/course fee or any details about the course without prior notice to the participants.


  • From 1 Oct 2023, attendance-taking for SkillsFuture Singapore (SSG)'s funded courses must be done digitally via the Singpass App. More information may be viewed here.
FD: Full day
AM: Morning
PM: Afternoon
EVE: Evening