Generative AI for Manufacturing* (24 Hours)

*This is a non-WSQ module.

This programme is co-organised with Amazon Web Services.
This programme is in collaboration with the Sectoral AI Centre of Excellence for Manufacturing (AIMfg).
This module is one of five in the AI in Manufacturing (AIM) programme. Complete all five AIM modules to qualify for an exemption from one Post-Diploma Certificate (PDC) requirement of the Specialist Diploma in Smart Manufacturing at Ngee Ann Polytechnic. Find out more.

Introduction

Artificial Intelligence, particularly Generative AI and Agentic AI, is increasingly transforming how organisations operate across various industries. In modern manufacturing environments, large amounts of data are generated from sensors, production systems, quality inspections, and maintenance records. Extracting actionable insights from this data can be quite challenging.

This 3-day course is designed as a hands-on, application-focused experience for technical and domain professionals who want to move beyond theoretical concepts and into real implementation. It offers a beginner-friendly pathway, taking learners from the foundations of generative AI to building agentic AI prototypes specifically for manufacturing. Participants are expected to have a basic comfort level with cloud-based tools and should possess beginner-level proficiency in Python.

About the Programme

The course equips learners with practical and career-relevant skills to design and implement agentic AI solutions specifically for the manufacturing sector.

Stage 1: Foundations of Generative AI and Agentic Systems
Participants will explore the foundations of generative AI, including foundation models, embeddings, and prompt engineering, and reinforce them through a prompt-engineering lab and responsible-AI guardrails. They then progress from large language models to agents, and are introduced to tool use, memory, and multi-agent concepts through a hands-on agent-building workshop.
Stage 2: Building Agentic AI Solutions for Manufacturing
Participants will build agentic AI solutions using modern agentic services and frameworks, and apply them to a real industrial use case. Through guided workshops, they implement an end-to-end manufacturing solution (for example, predictive maintenance) for manufacturing on a managed cloud AI platform, such as the AWS platform.
Stage 3: RAG Workflows, Evaluation, and Multi-Agent Diagnostics
Participants will implement a manufacturing-focused Retrieval-Augmented Generation (RAG) workflow in a hosted notebook/lab environment. They will evaluate and tune retrieval methods for generation quality and extend the solution into a simple multi-agent workflow using LangGraph for diagnostics, potential cause analysis, and recommended actions. Learners will have the ability to leverage large language models (LLMs) to apply them to manufacturing use cases without the need for finetuning

The course concludes with a guided mini project in which trainees will work in small groups to build a simple multi-agent agentic AI application for a manufacturing scenario. This project will cover the diagnostic process, potential causes of issues, and suggest recommended checks or actions.

Who Should Attend

This course is ideal for manufacturing and industrial organisations eager to harness the power of generative AI and agentic AI to significantly boost operational efficiency, enhance equipment reliability, assure quality, and improve decision-making capabilities. It caters to a broad audience, including:

Technical professionals (engineers, developers, and data/automation experts) tasked with bringing innovative prototypes to life.
Non-technical stakeholders (leaders and process owners) who must assess the feasibility, value, and potential risks of adopting these transformative technologies.

Course Outline

The programme employs the Learn-Practise-Implement™ (LPI™) pedagogy, where fundamental knowledge and principles taught will be reinforced with hands-on practices.

Key focus areas or applications:

RAG Development
Building LLM Applications
LangGraph for Multi-agents
AI Agent Fundamentals
Cloud-based Tools for AI
Generative AI

Upon Completion of This Course

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, Course Fees and How They Are Calculated

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 $2,400 before funding and prevailing GST.

Nett Course Fee

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
$2,616	$784.80	$304.80	$304.80

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.

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.

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.

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 ASTAR 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	$2,400	$2,400	$2,400	$2,400
Funding Support	Not Applicable	($1,680)	($2,160)	($2,160)
Nett Course Fee	$2,400	$720	$240	$240
GST 9%	$216	$64.80*	$64.80*	$64.80*
Total Nett Course Fee Payable to Training Provider	$2,616	$784.80	$304.80	$304.80

* Based on 30% of Full Course Fee

About the Trainers

Registration

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

Contact Us

Technical Enquiries	General Enquiries
Dr Nan Zhou Myo Lee Email: nan_zhou_myo_lee@a-star.edu.sg	Dr LIM Cheng Leong, Email: lim_cheng_leong@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
Generative AI for Manufacturing (24 hours)	TGS-2026063853	10 Nov 2026 - 3 Dec 2026	SIGN UP Now Registration for the Nov 2026 intake closes on 27 Oct 2026.

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

: Full day

: Morning

: Afternoon

: Evening

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