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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
  • UTAP
  • 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.

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 Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.

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

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year.

Submit UTAP Claim

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

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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

  • What are AI agents and agentic AI, and how they differ from single-turn generative AI
  • Use cases of agentic AI across the product development lifecycle
  • Evaluate various agentic AI builders to compare their strengths and limitations
  • Apply agentic AI to market and competitor research, customer needs discovery and user personas

Topic 2: Building and Optimising Agentic AI Product Development Workflows

  • Fundamentals of building an agentic AI workflow with a visual agent builder
  • Design multi-agent workflows that coordinate research, design, development, documentation and quality assurance
  • Translate product ideas into requirements, user stories, journey maps, specifications and prototypes
  • Testing the performance of an agentic AI workflow
  • Apply optimisation techniques to enhance the performance of agentic AI

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

  • Deploy agentic AI solutions into product team workflows and stakeholder feedback loops
  • Use agentic AI to evaluate prototypes, analyse user feedback, detect product gaps and monitor KPIs
  • Evaluate the benefits and trade-offs of deploying agentic AI
  • Human oversight, data quality, responsible AI practices, security, governance and validation of AI-generated outputs

Assessment

  • Written Exam
  • Practical Exam

Course Info

Promotion Code

Promo or discount cannot be applied to WSQ courses

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

Softtware: Windows / Mac

Hardware: Laptop

About Progressive Wage Model (PWM)

The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity. 

Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

For more information on PWM, please visit MOM site.

Funding Eligility Criteria

Individual Sponsored Trainee Employer Sponsored Trainee
  • Singapore Citizens or Singapore Permanent Residents aged 21 and above
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.
  • Singapore Citizens or Singapore Permanent Residents who are DIRECT EMPLOYEE of the sponsoring company.
  • From 1 October 2023, attendance-taking for SWDA's (formerly SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
  • Trainee must pass all prescribed tests / assessments and attain 100% competency.
  • We reserves the right to claw back the funded amount from the employer if trainee did not meet the eligibility criteria.

 SkillsFuture Credit: 

  • Eligible Singapore Citizens can use their SkillsFuture Credit to offset course fee payable after funding.

 PSEA:

  • To check for Post-Secondary Education Account (PSEA) eligibility, goto mySkillsFuture portal and search for this course code.
  • Scroll down to "Keyword Tags" to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.  
  • And if there is no “PSEA” under keyword tags, the course is ineligible for PSEA. 
  • Not all courses are eligible for PSEA funding.

 Absentee Payroll (AP) Funding: 

  • $4.50 per hour, capped at $100,000 per enterprise per calendar year.
  • AP funding will be computed based on the actual number of training hours attended by the trainee.

 SFEC:

  • If the Training Provider has submitted an enrolment for course fee grant claim in Training Partners Gateway (TPGateway), SWDA would be able to derive SFEC funding based on this record. There is no need for enterprise to submit any claim request and the SFEC claim will be automatically generated and disbursed.
  • Where there is no such record, eligible employers are required to submit an SFEC claim after course completion via the SFEC microsite.
  • SkillsFuture Enterprise Credit (SFEC) Microsite 

Appeal Process

  1. The candidate has the right to disagree with the assessment decision made by the assessor.
  2. When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
  3. If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
  4. If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
  5. If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
  6. If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
  7. The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
  8. The candidate must lodge the appeal within 7 days, giving reasons for appeal 
  9. The assessor can help the candidate with writing and lodging the appeal.
  10. he assessment manager will collect information from the candidate & assessor and give a final decision.
  11. A record of the appeal and any subsequent actions and findings will be made.
  12. An Assessment Appeal Panel will be formed to review and give a decision.
  13. The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
  14. The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
  15. Please click the link below to fill up the Candidates Appeal Form.

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

Tan Woei Ming is an accomplished data scientist and AI engineer with over 15 years of experience in artificial intelligence, machine learning, and data-driven innovation. Holding 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, he has led AI initiatives in predictive analytics, automation, and process optimization across the semiconductor and manufacturing industries. His expertise lies in translating complex AI technologies into practical business applications, enabling organizations to innovate through data insights and intelligent automation.
Yeo Hwee Theng is a data science leader and AI strategist with extensive experience in driving enterprise analytics, AI adoption, and data architecture initiatives across healthcare, finance, and government sectors. As the Data & Analytics Product Lead at Amplify Health, she leads large-scale data transformation and machine learning projects focused on improving business outcomes through data-driven decision-making. Her previous roles include AI & Data Architect at Huawei International and Senior Data Scientist at DataRobot, where she implemented 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).
Teh Siew Yee is an experienced adult educator and corporate trainer specializing in business communication, workplace effectiveness, and professional development. With years of experience across both corporate and training environments, she has helped learners enhance their skills in problem-solving, collaboration, and interpersonal communication. Her ability to translate complex concepts into clear, practical strategies ensures that participants can immediately apply their learning in the workplace. As an ACLP-certified trainer, Siew Yee delivers WSQ courses with a strong focus on learner engagement and workplace application. She integrates case studies, role-plays, and reflective exercises into her sessions, ensuring participants develop not only knowledge but also confidence in real-world contexts. By combining her corporate experience with adult education expertise, she empowers learners to improve workplace efficiency, strengthen teamwork, and achieve personal and organizational success.

Truman Ng is a cloud computing and AI systems integration specialist with more than two decades of experience in IT infrastructure, DevOps, and digital transformation. A PMP, ACTA, and Huawei HCIE-certified professional, he has designed and deployed AI-enabled systems that bridge automation, data intelligence, and cloud architecture. Truman’s expertise lies in integrating AI agents with secure, scalable backend systems for enterprise applications.
In “Agentic AI for Product Development,” Truman focuses on the technical implementation of agentic AI within enterprise environments. His sessions highlight tool and API integration, deployment security, governance, and performance optimization for autonomous agent systems. Through real-world examples and demonstrations, he enables learners to build robust, cloud-ready agentic solutions that plug into existing product development pipelines.

James Lee is a digital media and IT educator with over 20 years of experience in multimedia production, creative technology, and AI-driven content design. An Adobe Certified Expert and ACLP-qualified trainer, he has taught digital communication, user experience, and AI applications in creative industries. His teaching approach combines visual design, automation, and human-AI interaction principles to enhance communication and user engagement.
In “Agentic AI for Product Development,” James helps participants understand how to use agentic AI to design product experiences that improve usability and engagement. His sessions emphasize prompt design, AI-assisted prototyping, journey mapping, and user-feedback analysis. By blending creativity with technical design, he guides learners to shape products that address real user needs and reflect a coherent brand experience.

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