AIM-READY: AI-Powered Demand Forecasting* (16 Hours)

*This is a non-WSQ module.
Aim Ready AI Powered Demand Forecasting

Introduction

AI-powered demand forecasting is reshaping how manufacturers and supply chain teams plan, respond, and compete. But knowing where to start — and whether your organisation is truly ready — is often the hardest part.

AIM-Ready: AI-Powered Demand Forecasting is a 16-hour, practice-oriented programme designed to bridge that gap. You will assess your organisation’s readiness to adopt AI-powered demand forecasting, identify the right use cases for your context, and leave with a concrete implementation roadmap you can act on.

No coding. No model-building. Just practical frameworks, real-world case studies, and guided activities that move you from opportunity to action.

About the Programme

Rather than building AI models, participants focus on what matters most for adoption success — evaluating the right approaches, assessing organisational fit, and planning a credible path forward. You will work on a workplace-relevant demand forecasting use case throughout the programme, culminating in an AI adoption proposal and implementation roadmap you can bring back to your organisation.

By the end of this programme, you will be equipped to:

  • Identify and prioritise AI demand forecasting use cases based on your business challenges and expected value
  • Define a well-scoped use case with clear objectives, target outcomes, and measurable KPIs
  • Assess your demand-planning processes, data quality, enterprise systems, and organisational readiness
  • Evaluate forecasting approaches and explainability methods suited to different demand scenarios
  • Plan solution architecture, enterprise integration, and implementation requirements
  • Build a business case covering value, feasibility, risks, and deployment priorities
  • Develop a practical AI adoption proposal and implementation roadmap ready to present to stakeholders

Who Should Attend

This programme is designed for manufacturing and supply chain professionals driving demand planning improvement, digital transformation, or AI adoption — including demand, supply, and production planners; inventory and procurement managers; supply chain and operations managers; planning and data analysts; digital transformation and AI project leads; ERP and enterprise systems leads; and business leaders responsible for forecasting improvement.

No prior coding or AI experience is required. A working familiarity with demand forecasting, supply chain planning, inventory management, or manufacturing operations is recommended.

Course Outline

This programme is structured around six progressive stages that take you from spotting the right AI opportunities to building a roadmap your organisation can act on.

  • Identify AI Opportunities — Recognise and prioritise demand forecasting challenges where AI can deliver meaningful business value

  • Define an AI-Ready Use Case — Scope a well-defined use case with clear objectives, target outcomes, and measurable success criteria

  • Assess AI Readiness — Evaluate your demand-planning processes, data quality, enterprise systems, and organisational capability
  • Assess AI Solution Suitability — Evaluate forecasting approaches, explainability methods, and solution architecture for your specific context

  • Assess Implementation Feasibility — Determine business value, risks, integration requirements, and deployment priorities

  • Develop an Adoption Roadmap — Build a practical AI adoption proposal covering pilot scope, timeline, roles, validation, and next steps

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 course fee upon failure to meet either one of the criteria.

Pre-Requisites

  • 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 $1,600 before funding and prevailing GST.

Nett Course Fees

International
Participants		 Singapore Citizens aged 39 years and below, Singapore Permanent Residents and LTVP+ Holders Employer-sponsored and self-sponsored Singapore Citizens aged 40 years and above (MCES) ² SME-sponsored local employees (i.e Singapore Citizens, Singapore Permanent Residents and LTVP+ Holders) (ETSS) ¹
$1,744 $523.20 $203.20 $203.20
Nett course fees are after funding deductions and inclusive of GST. Please note that fees and funding amounts are subject to change.

Not sure which nett fee category applies to you? Use our checker to find out.

Access Checker

Long Term Visit Pass Plus (LTVP+) Holders

The Long Term Visit Pass Plus (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.
¹ Enhanced Training Support For Small & Medium Enterprise Scheme (ETSS)

The ¹Enhanced Training Support for Small & Medium Enterprises scheme (ETSS) supports company-sponsored participants with up to 90% course fee subsidies.  To qualify, both the employers and trainees must meet the following eligibility criteria.

  • Eligible Small & Medium Enterprises (SMEs) must meet all of the following conditions:
    • Registered or incorporated in Singapore
    • Employment size of not more than 200 employees, or annual sales turnover of not more than $100 million

  • SME-sponsored trainees must meet all of the following:
    • Singapore Citizen or Singapore Permanent Resident
    • Course fees are fully paid for by the employer
    • Trainee is not a full-time national serviceman
Further Information:
This scheme is intended for all organisations, including non-business entities not registered with ACRA, for example, Voluntary Welfare Organisations (VWOs), societies, etc. Only ministries, statutory boards, and other government agencies are NOT eligible under the Enhanced Training Support for SMEs Scheme. Sole proprietorships which meet all of the above criteria are also eligible.
² SkillsFuture Mid-Career Enhanced Subsidy (MCES)

The ²SkillsFuture Mid-Career Enhanced Subsidy (MCES) is meant for employer-sponsored and self-sponsored Singapore Citizens aged 40 years old and above.

Eligible Singapore Citizens can receive higher subsidies of up to 90% of course fees.
SkillsFuture Credit (SFC)

All Singapore Citizens aged 25 years old and above are eligible for SkillsFuture Credit (Opening Credit), which can be used to offset course fees (for self-sponsored registrations only).
SkillsFuture Credit (Mid-Career)

The SkillsFuture Credit (Mid-Career) is only applicable for the full A*STAR SkillsFuture Career Transition Programme (SCTP) enrolments, and cannot be used for standalone or individual module sign-ups.

How Course Fees are Calculated

TYPE CATEGORY OF INDIVIDUALS
International Participants  Singapore 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)
FUNDING SOURCE
 Not applicable for Funding Support SkillsFuture Funding (Baseline) SkillsFuture Mid-career Enhanced Subsidy (MCES) ² SkillsFuture Enhanced Training Support for SMEs (ETSS) ¹
Full Course Fee $1,600  $1,600  $1,600  $1,600 
Funding Support Not Applicable   ($1,120) ($1,440) ($1,440)
Nett Course Fee $1,600 $480  $160 $160
GST 9% $144  $43.20*  $43.20*  $43.20*
Total Nett Course Fee Payable to Training Provider $1,744 $523.20  $203.20  $203.20
* Based on 30% of Full Course Fee

About the Trainers

Dr Bao Hongyan
Dr Liu Ning
Ms Serina Zhao Fei
Dr Le Van Dang
Mr Teng Wei Yuen
Dr Bao Hongyan
Dr Bao Hongyan
Scientist
A*STAR ARTC

Dr Bao Hongyan is a Scientist with A*STAR ARTC’s Digital Supply Chain (DSC) Group, where she develops AI-driven solutions for demand forecasting and supply chain analytics. Her work focuses on applying machine learning and data mining techniques to improve forecasting accuracy and support data-driven supply chain planning. Dr Bao holds a Ph.D. in Computer Science from King Abdullah University of Science and Technology (KAUST), Saudi Arabia, as well as an M.Sc. in Electronics and Communication Engineering from the University of Chinese Academy of Sciences and a B.Eng. in Microelectronics from Xidian University. Her research interests include trustworthy AI, adversarial machine learning, cybersecurity, and large-scale data mining.

Dr Liu Ning
Dr Liu Ning
Senior Scientist
A*STAR ARTC

Dr Liu Ning is the Deputy Group Manager of the DSC Group at A*STAR ARTC. He received his B.Eng. from Xi’an Jiaotong University in 2012 and his Ph.D. from the National University of Singapore (NUS) in 2016. Prior to joining ARTC, he served as a Research Fellow at NUS. He currently leads R&D projects and initiatives within the Digital Manufacturing Division, focusing on advanced manufacturing technologies such as supply chain analytics, sustainable manufacturing, data-driven modelling and optimisation, and artificial intelligence. 

Ms Serina Zhao Fei
Ms Serina Zhao Fei
Lead Research Engineer
A*STAR ARTC

Ms Serina Zhao Fei is a Lead Research Engineer with A*STAR ARTC’s DSC Group, where she develops supply chain and AI solutions and supports end-to-end supply chain transformation initiatives. She works closely with industry partners to assess supply chain operations and translate business requirements into practical technical solutions and implementation roadmaps. Ms Serina has successfully led and delivered numerous industry projects in recent years. She holds a B.Eng. in Materials Science from Xi’an University of Architecture and Technology and brings over 20 years of leadership experience in highly regulated industries, including medical devices and semiconductor electronics, in Singapore.

Dr Le Van Dang
Dr Le Van Dang
Senior Scientist
A*STAR ARTC

Dr Le Van Dang is a Senior Scientist at A*STAR ARTC. He earned his PhD in Computer Engineering from the Sirindhorn International Institute of Technology (SIIT) at Thammasat University in Thailand. Dr. Dang specialises in process optimisation, algorithm development, and mathematical programming. His work and research interests primarily focus on supply chain resilience, risk management, supply chain digital twin, network optimisation, and AI applications in supply chain management.

Mr Teng Wei Yuen
Mr Teng Wei Yuen
Lead Research Engineer
A*STAR ARTC

Mr Teng Wei Yuen is a Lead Research Engineer with A*STAR ARTC’s DSC Group. He is responsible for overseeing the end-to-end order fulfilment section and specialises in emerging technologies, including blockchain, AI, cloud technology, and mobile app development. Mr Teng holds a M.Sc. in Electrical Engineering from NUS and has played a crucial role in developing digital solutions such as eDataLogger and the Digital Workflow Automation system. These innovative solutions have been successfully implemented in over 90 local companies, resulting in significant productivity enhancements through streamlined forms and workflow processes.

Registration

Sign up now

  • Please register for this course through our online form: Course Registration Form for Public Classes.
  • For the first question, please select "Modular Programmes (Standalone Modules)".
  • Applicants will be placed on our waiting list if the course does not have an upcoming scheduled intake.
  • When the next intake is confirmed, a confirmation email with payment information will be sent to applicants to finalise their participation.

Collateral

Download brochure

AI-Powered Demand Forecasting

Contact Us

Technical Enquiries General Enquiries

Dr BAO Hongyan,
Email: bao_hongyan@a-star.edu.sg

 Ms Serina ZHAO Fei,
Email: zhao_fei@a-star.edu.sg

Schedule

Module
 Skills Course Reference Number Next Intake(s)' Training Period
(Click on the dates to view their schedules)		 Registration Status 
  • AIM-READY: AI-Powered Demand Forecasting (16 hours)
 TGS-2026065358 The schedule for the next intake is still in the planning stage.  

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

Announcement:

  • From 1 Oct 2023, attendance-taking for SWDA-approved/SWDA-funded courses must be done digitally via the Singpass App. More information may be viewed here.
  • Participants will be provided with digital course materials when attending our courses. Please note that printed copies will not be available.
Sessions
FD: Full day
AM: Morning
PM: Afternoon
EVE: Evening
 

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