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WSQ Build a Generative AI LLM-Powered Chatbot to Enhance Customer Service

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 TSC

Learning Outcomes

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

  • LO1: Evaluate various LLM-powered chatbot builders to compare their strengths and limitations.
  • LO2: Apply optimization techniques to enhance the performance of LLM-powered chatbot.
  • LO3: Evaluate the benefits and trade-offs of deploying LLM-powered chatbot.
Download Course Brochure

Certification

  • Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.
  • 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 - Build a Generative AI LLM-Powered Chatbot to Enhance Customer Service

Course Code: TGS-2024045799
  • WSQ
  • SkillsFuture Credit
  • PSEA
  • UTAP
  • SFEC
  • Absentee Payroll
  • MCES

6 Review(s) | Add Your Review

What's This Course About

This comprehensive course equips participants with the expertise to evaluate, build, and optimize Large Language Models (LLM) powered chatbots, aimed at transforming customer service operations. Participants will delve into the fundamentals of Generative AI (GAI) and LLM, understand the practical applications of LLM-powered chatbots, and explore various no-code chatbot builders to compare their strengths and limitations. The course covers the essential steps for creating a high-performing chatbot, including using visual builders, testing, and optimizing chatbot performance to ensure efficient customer interactions.

Furthermore, the course provides insights into deploying chatbots across different channels, including the basics of JavaScript for website integration, and evaluates the benefits and trade-offs of implementing such technologies in customer service. By the end of this course, learners will be equipped with the knowledge and skills to apply optimization techniques and deploy a generative AI-powered chatbot that enhances customer interaction and service.

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.Click here to submit SkillsFuture Enterprise Credit

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. Click here for SkillsFuture Credit submission

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. Click here to submit UTAP

PSEA

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

To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2024042600)
  • 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 and email to us. 

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: No-Code LLM-Powered Chatbots

  • What is Large Language Models (LLM) and Generative AI (GAI)
  • Use cases of LLM-powered chatbots
  • Evaluate various No-code LLM-powered chatbot builders

Topic 2: Build a LLM-Powered Chatbot

  • Fundamentals of building a LLM-powered chatbot with visual chatbot builder
  • Testing the performance of chatbot
  • Optimizing the chatbot’s performance

Topic 3: Deploy and Evaluate LLM-powered Chatbot

  • Deploy chatbot on various channels
  • Basic Javascript script for website deployment
  • Evaluate the benefits and trade-offs of implementing chatbot

Final Assessment

  • Written Assessment - Short Answer Questions (WA-SAQ)
  • Practical Performance (PP)

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 SkillsFuture Singapore's (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 SkillsFuture Singapore's (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), SSG 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

  • Customer Service Manager
  • Chatbot Developer
  • AI Product Manager
  • Digital Marketing Specialist
  • Customer Experience Strategist
  • IT Support Specialist
  • Web Developer
  • AI Implementation Consultant
  • Technical Support Engineer
  • Chatbot Design Consultant
  • UX/UI Designer for Chatbots
  • Data Analyst
  • Software Engineer
  • Business Analyst
  • Innovation Manager
  • Project Manager
  • AI Researcher
  • Customer Insights Analyst
  • Quality Assurance Engineer
  • E-commerce 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 LLM-based chatbots with secure, scalable backend systems for enterprise applications.
In “Build a Generative AI LLM-Powered Chatbot to Enhance Customer Service,” Truman focuses on the technical implementation of AI chatbots within enterprise environments. His sessions highlight backend integration, deployment security, and performance optimization for AI conversational systems. Through real-world examples and demonstrations, he enables learners to build robust, cloud-ready chatbot solutions that deliver seamless and intelligent customer support.

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 “Build a Generative AI LLM-Powered Chatbot to Enhance Customer Service,” James helps participants understand how to design intuitive chatbot interfaces that improve user experience and engagement. His sessions emphasize prompt design, conversational flow, and integrating generative AI with visual communication. By blending creativity with technical design, he guides learners to create chatbots that communicate naturally, reflect brand personality, and deliver meaningful customer interactions.

Review

Customer Reviews (6)

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