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Agentic AI for Product Development

Course Information

  • Sessions 2 days
  • Duration 16 hrs
  • Level Beginner
  • Assessment 2 hrs

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

Skills Framework

TSC Title
Automation Management in Product Development
TSC Code
ICT-TEM-4035-1.1

Funding Validity

Funding for this course is valid from 16 May 2024 to 15 May 2028. Register and complete the course within this period to qualify for funding support.

Learning Outcomes

By end of the course, learners should be able to:

  • LO1: Evaluate various Agentic AI builders to compare their strengths and limitations.
  • LO2: Apply optimization techniques to enhance the performance of Agentic AI.
  • LO3: Evaluate the benefits and trade-offs of deploying Agentic AI.

Course Brochure

Download Course Brochure

Certification

  • Certificate of Achievement from Tertiary Infotech Academy Pte Ltd - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Achievement from Tertiary Infotech Academy Pte Ltd.
  • OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ - Agentic AI for Product Development

Course Code: TGS-2024045799
  • WSQ
  • SFC
  • PSEA
  • SFEC
  • Absentee Payroll
  • MCES

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What's This Course About

This course equips participants with practical skills to apply agentic AI across the product development lifecycle, from opportunity discovery and concept creation to prototyping, testing, launch, and continuous improvement. Learners will explore how autonomous AI agents can perform multi-step tasks, coordinate workflows, analyse information, and support product teams in making faster, evidence-based decisions.

Participants will use agentic AI to conduct market and competitor research, identify customer needs, develop user personas, generate product concepts, and prioritise features. They will learn to translate product ideas into requirements, user stories, journey maps, specifications, development plans, and prototypes that align with business objectives and user expectations.

The course also covers designing multi-agent workflows for coordinating research, design, development, documentation, quality assurance, and stakeholder feedback. Learners will apply agentic AI to evaluate prototypes, analyse user feedback, detect product gaps, monitor key performance indicators, and recommend improvements throughout iterative development cycles.

Emphasis is placed on human oversight, data quality, responsible AI practices, security, governance, and the validation of AI-generated outputs. Through hands-on projects, participants will develop an AI-assisted product concept and supporting development workflow. By the end of the course, learners will be able to use agentic AI to improve collaboration, reduce repetitive work, shorten development cycles, and create products that better address customer and market needs.

This course is part of our AI training in Singapore, where you can browse all our AI courses. See more agentic AI training.

WSQ Funding

Full Fee $800.00 Before GST
GST $72.00 9% of fee
Baseline Nett $472.00 SG/PR age 21+ · 50% funded
MCES / SME Nett $312.00 SG age 40+ · 70% funded
SkillsFuture Enterprise Credit (SFEC)

Eligible companies can use their $10,000 SFEC to cover up to 90% of out-of-pocket course fees for classes ending on or before 30 Nov 2026. A redesigned SFEC starts on 1 Dec 2026.

View on SkillsFuture for Business

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used.

Direct Application on SkillsFuture Portal

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

Check PSEA Eligibility

  • Scroll down to “Keyword Tags” to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form, then submit the completed form to us:

PSEA Withdrawal FormSubmit PSEA Form

Course FeeBefore Funding

$800.00 (GST-exclusive)
$872.00 (GST-inclusive)

Course Date

* Required Fields

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Cancellation & Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom.

Course Details

Course Details

What You'll Learn

Topic 1: Evaluating Agentic AI Tools for Product Research and Development

Topic 2: Building and Optimising Agentic AI Product Development Workflows

Topic 3: Deploying and Evaluating Agentic AI-Powered Product Solutions

Assessment

  • Written Exam
  • Practical Exam

Course Info

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Minimum Software/Hardware Requirement

Software:

You will need the following for this course:

Hardware: Windows PC or Mac laptop

Funding Eligibility Criteria

Self-sponsored learners (individuals)

  • Singapore Citizens and Singapore Permanent Residents aged 21 and above.
  • Up to 50% course fee funding. Singapore Citizens aged 40 and above receive up to 70% under the Mid-career Enhanced Subsidy (MCES).
  • Singapore Citizens aged 25 and above can pay the remaining fee with SkillsFuture Credit.

Company-sponsored learners

  • Singapore Citizens and Singapore Permanent Residents who are direct employees of the sponsoring company.
  • Up to 50% course fee funding, or up to 70% for employees of SMEs (Enhanced Training Support for SMEs) and for Singapore Citizens aged 40 and above. An SME has no more than 200 employees or an annual turnover of no more than $100 million.
  • Employers can also claim Absentee Payroll funding for employees who attend during working hours.
  • Eligible companies can offset their out-of-pocket fees with SkillsFuture Enterprise Credit (SFEC).

Conditions for all funded learners

  • Attendance is taken digitally with Singpass for every session, including the assessment.
  • You must complete the course and pass all assessments (assessed as Competent).
  • If these conditions are not met, the funding is clawed back and the learner or employer pays the full course fee.
  • 9% GST is charged on the full course fee before funding.
  • Promo and discount codes cannot be used on funded courses.
  • Any balance after funding can be paid in cash, with SkillsFuture Credit, with PSEA (Singapore Citizens with a PSEA).

How to Apply SkillsFuture Credit Claim for Individuals

Singapore Citizens aged 25 and above can use their SkillsFuture Credit (base tier) to pay the course fee after funding. The $4,000 mid-career top-up cannot be used for this course.

  1. Register for this course as self-sponsored and tell us you will use SkillsFuture Credit. Do not pay the amount you plan to claim.
  2. We email you an invoice showing the course fee after funding.
  3. From 60 days before the course starts, and no later than the course start date, log in to MySkillsFuture with Singpass and click Claim credits.
  4. Click Submit a Claim and search for this course by its course code, TGS-2024045799.
  5. Select your class start date, enter the course fee payable after funding and the amount of credit to claim, then upload the invoice (PDF, JPG or PNG, under 4MB).
  6. Review, accept the terms and click Agree and Submit. The credit is paid directly to us; processing can take up to 14 working days.

Changing or withdrawing: cancel the claim on MySkillsFuture at least one day before the course starts. If your class date changes, cancel the claim and submit a new one with the new date.

How to Apply SkillsFuture Enterprise Credit (SFEC)

SFEC helps companies pay for employee training. The current SFEC ends on 30 November 2026, and a redesigned SFEC starts on 1 December 2026.

Current SFEC: classes ending on or before 30 November 2026

  • Eligible companies received a one-off $10,000 credit, notified by letter to their Corppass administrator. Eligibility generally required at least 3 Singapore Citizen or PR employees and Skills Development Levy contributions.
  • SFEC covers up to 90% of the company's out-of-pocket course fee after other subsidies.
  1. Check your company's SFEC eligibility and balance on EnterpriseSG.
  2. Register your Singapore Citizen or PR employee for a class that ends by 30 November 2026, as company-sponsored, and pay the course fee after funding.
  3. Your employee attends and completes the course. We submit the attendance and assessment results to SWDA.
  4. No separate claim is needed. SFEC is calculated automatically once the course fee grant is approved and is paid quarterly to your company's IRAS GIRO or PayNow Corporate account.

Any unused balance of the current SFEC expires on 30 November 2026.

Redesigned SFEC from 1 December 2026

Companies with at least 3 resident employees receive a fresh $10,000 in an online SFEC wallet that offsets out-of-pocket fees upfront at enrolment, instead of reimbursing them afterwards. SWDA has not yet published the support rates and claim steps; see OurWorkforce or our SFEC guide.

How to Apply PSEA

Singapore Citizens with a Post-Secondary Education Account (PSEA), which stays open until around the year you turn 31, can use it to pay the course fee after funding for PSEA-approved courses. You can also use a sibling's PSEA after your own has been used up.

  1. Check that this course shows the PSEA tag on its MySkillsFuture page.
  2. Check your PSEA balance on MOE's Student Finance System with Singpass.
  3. Download and complete the PSEA withdrawal form, then submit it to us.
  4. We submit the withdrawal request to MOE. You (and your sibling, if you are using their account) authorise it in the Student Finance System. Nothing is withdrawn without this authorisation.
  5. MOE pays us directly. If you have already paid, we refund the amount covered by PSEA.

More details: MOE PSEA overview.

Appeal Process

If you disagree with an assessment decision, you have the right to appeal.

  1. When the assessor gives you feedback, say whether you agree with the outcome. If you agree, you and the assessor sign the Assessment Summary Record; if you disagree, do not sign it.
  2. Discuss the decision with the assessor or the assessment manager first.
  3. If you are still not satisfied, tell the assessor you intend to appeal. The assessor records this in the feedback section of the Assessment Summary Record and informs the assessment manager.
  4. Lodge your appeal within 7 days, giving your reasons, using the Candidate Appeal Form. The assessor can help you write and lodge it.
  5. An Assessment Appeal Panel reviews the information from you and the assessor and makes a decision. A record of the appeal and its outcome is kept.
  6. You will be told the outcome within 2 weeks of lodging the appeal. The panel's decision is final.

Job Roles

Job Roles

  • Product Manager
  • Product Owner
  • AI Product Manager
  • Product Development Engineer
  • Digital Product Manager
  • UX/UI Designer
  • User Researcher
  • AI Implementation Consultant
  • Product Marketing Manager
  • Solution Architect
  • Web Developer
  • Data Analyst
  • Software Engineer
  • Business Analyst
  • Innovation Manager
  • Project Manager
  • AI Researcher
  • Customer Insights Analyst
  • Quality Assurance Engineer
  • R&D Manager

Trainers

Trainers

Taking a product from idea to launch is something Dr. Alfred Ang does repeatedly, and increasingly with AI agents in the loop. As founder of Tertiary Courses and a serial entrepreneur who also founded OSWeb2Design Singapore Pte Ltd, Tertiary Robotics and Tertiary Courses Malaysia, he has built products and businesses from scratch. Today he is Managing Director, CIO, CTO and Chief Instructional Designer of Tertiary Infotech Academy Pte Ltd, and a full-stack AI developer and Agentic AI solution architect specialising in multi-agent systems built with frameworks such as CrewAI, Microsoft AutoGen, the OpenAI Agents SDK, Claude Agent SDK and n8n. His public GitHub portfolio of more than 300 repositories reads like a product pipeline: native mobile apps such as tapcardapp and scannerapp on the App Store and hrmsapp_android on Google Play; full-stack platforms such as tapcard and ai-exams; and AIInterviewing, which lets users practise interviews with an AI hiring manager for roles including Product Manager. He holds a PhD in Electrical Engineering from NUS and is a certified PMP and CSM, a Microsoft Certified AI Engineer Associate (AI-102) and Power BI Data Analyst (PL-300), and an AWS Certified AI Practitioner. He also brings research discipline from more than 20 peer-reviewed papers and more than 20 US patents as co-inventor, gained in the defence, electronics and semiconductor industries. He is also an ACTA-certified trainer and DACE-certified curriculum developer who designs WSQ programmes aligned to the Skills Framework.

In WSQ - Agentic AI for Product Development, Dr. Ang shows product teams how autonomous AI agents can carry multi-step work across the lifecycle while people keep ownership of decisions. The first topic evaluates agentic AI tools for product research and development, using agents for market and competitor research, identifying customer needs, developing user personas and generating product concepts. Learners then build and optimise agentic product development workflows, prioritising features, coordinating tasks and supporting prototyping and testing, before the final topic on deploying and evaluating agentic AI-powered product solutions, including launch and continuous improvement. His own experience shipping apps and platforms lets him show where agents genuinely speed up discovery and iteration and where they mislead, for example when research is not grounded in real sources or when synthetic user feedback replaces real customers. His PMP and Scrum background helps learners fit agents into existing product and delivery processes rather than bolting them on. Sessions are hands-on: learners design and run agent workflows against a realistic product challenge and evaluate the outputs critically. As a WSQ course, it also prepares learners for assessment, and participants leave with a practical approach to faster, evidence-based product decisions. He also encourages learners to define clear success measures before launching an agent, so its contribution to research, design and testing can be judged on evidence rather than enthusiasm. To see the products and agent projects he has built, learners can view his GitHub portfolio at https://github.com/alfredang and connect with him on LinkedIn at https://www.linkedin.com/in/angchewhoe/

Yeo Hwee Theng is a data science and AI product leader with extensive experience building enterprise AI and analytics solutions. As Data & Analytics Product Lead at Amplify Health, she has led large-scale data and machine learning initiatives across the healthcare and finance sectors. Her earlier roles as AI & Data Architect at Huawei International and Senior Data Scientist at DataRobot involved architecting AI systems that deliver measurable business value and implementing advanced AI and analytics solutions across the Asia-Pacific region. She holds a Master of Technology in Enterprise Business Analytics from the National University of Singapore and an Advanced Certificate in Learning and Performance (ACLP).

In Agentic AI for Product Development, she bridges AI design with the day-to-day reality of enterprise product teams. Learners first evaluate agentic AI tools for product research and development, using agents for market and competitor research, opportunity discovery and requirements generation. They then build and optimise agentic workflows that support concept creation, prototyping and testing, before deploying and evaluating AI-powered product solutions against clear measures. Drawing on her product leadership and technical insight, she helps participants see where autonomous agents can shorten development cycles and where human judgement remains essential, so they leave able to introduce agentic AI into their own product lifecycle and support faster, evidence-based decisions.

Tan Woei Ming is an AI engineer and data scientist with over 15 years of experience in machine learning, deep learning and intelligent automation. He has led AI-driven projects across predictive analytics, natural language processing and automation within the semiconductor and manufacturing industries. His expertise spans Python, TensorFlow, PyTorch and LangChain, enabling him to bridge advanced AI techniques with real-world business applications. He holds a Master's in Intelligent Systems from the National University of Singapore (NUS) and a First-Class Honours in Electrical and Electronic Engineering from NTU.

In WSQ - Agentic AI for Product Development, Woei Ming teaches participants to use autonomous AI agents for multi-step product development tasks. Learners evaluate agentic AI tools for product research and development, build and optimise agentic product development workflows, and then deploy and evaluate agentic AI-powered product solutions. His sessions focus on comparing agent builders, orchestrating multi-agent workflows and improving agent performance for reliability and contextual accuracy. Through hands-on exercises grounded in his experience of process optimisation, he helps learners build agentic systems that accelerate research, prototyping and iteration while keeping outputs accurate and measurable.

Teh Siew Yee is a digital transformation and data analytics leader with more than two decades of experience in technology, finance and manufacturing. Having held senior positions at Standard Chartered, Hewlett-Packard and TikTok, Siew Yee brings a wealth of experience in AI governance, data management and enterprise analytics. Siew Yee holds a Master of IT in Business (Artificial Intelligence) from Singapore Management University and is a certified ACLP trainer whose WSQ sessions use case studies, role-plays and reflective exercises to connect learning to the workplace.

In Agentic AI for Product Development, Siew Yee combines business strategy with AI technology to show how autonomous agents can support each stage of the product lifecycle, from opportunity discovery and concept creation to prototyping, testing and launch. Learners evaluate agentic AI tools for product research and development, then build and optimise agentic workflows using prompt engineering, task decomposition and tool integration. The course concludes with deploying and evaluating agentic AI-powered product solutions. Siew Yee's practical approach equips product teams to design goal-directed agent workflows that improve product quality and shorten time to market while keeping human judgement at the centre.

Truman Ng specialises in integrating AI agents with secure, scalable backend systems for enterprise applications. A cloud computing and AI systems integration specialist with more than two decades of experience in IT infrastructure, DevOps and digital transformation, he has designed and deployed AI-enabled systems that bring together automation, data intelligence and cloud architecture. He holds PMP and Huawei HCIE certifications and is an ACTA-certified trainer who teaches through real-world examples and demonstrations of agentic AI implemented within enterprise environments.

In WSQ Agentic AI for Product Development, Truman shows participants how to apply agentic AI across the product development lifecycle, from opportunity discovery and concept creation to prototyping, testing, launch and continuous improvement. Learners evaluate agentic AI tools for product research and development, use agents for market and competitor research, and build and optimise agentic workflows that support faster, evidence-based decisions. They then deploy and evaluate agentic AI-powered product solutions. His focus on tool and API integration, deployment security, governance and performance optimisation helps learners build robust, cloud-ready agentic solutions that plug into existing product development pipelines.

Review

Customer Reviews (6)

Average Rating: 5.0/5 Review by Course Participant/Trainee
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Kesston is a very fun and engaging instructor (Posted on 6/14/2026)
Average Rating: 5.0 Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Kesston was humorous and candid (Posted on 4/2/2026)
Average Rating: 5.0 Review by Course Participant/Trainee
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2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Kesston was humorous and candid (Posted on 4/2/2026)
willl recommend Review by Course Participant/Trainee
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. (Posted on 5/23/2025)
willl recommend Review by Course Participant/Trainee
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. (Posted on 5/23/2025)

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