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

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)

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

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.

• 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

Tan Woei Ming: Tan Woei Ming is an AI engineer and data scientist with more than 15 years of experience in machine learning, deep learning, and intelligent automation. Holding a Master’s in Intelligent Systems from the National University of Singapore (NUS), he has led numerous AI-driven projects across predictive analytics, NLP, and automation within the semiconductor and manufacturing industries. His expertise spans Python, TensorFlow, PyTorch, and LangChain, enabling him to bridge cutting-edge AI research with real-world business applications.

In “Build a Generative AI LLM-Powered Chatbot to Enhance Customer Service,” Woei Ming teaches participants how to design and deploy conversational AI systems powered by large language models (LLMs). His sessions focus on fine-tuning pre-trained models, integrating APIs, and optimizing chatbots for contextual understanding and responsiveness. Through hands-on exercises, he empowers learners to develop scalable AI chatbots that enhance customer engagement and streamline support processes.

Yeo Hwee Theng: Yeo Hwee Theng is a data science and AI product leader with extensive experience in building enterprise AI and analytics solutions. As the Data & Analytics Product Lead at Amplify Health, she has led large-scale data and machine learning initiatives across healthcare and finance sectors. Her previous roles at Huawei International and DataRobot involved architecting AI systems that deliver measurable business value. She holds a Master of Technology in Enterprise Business Analytics from the National University of Singapore (NUS).

In “Build a Generative AI LLM-Powered Chatbot to Enhance Customer Service,” Hwee Theng focuses on bridging AI design with real-world application in enterprise contexts. Her sessions explore chatbot architecture, NLP-driven intent recognition, and the integration of LLMs with business workflows. With her strategic and technical insights, she guides learners to build intelligent, human-like customer service chatbots that deliver efficiency and personalization at scale.

Teh Siew Yee: Teh Siew Yee is a digital transformation and data analytics leader with over 20 years of experience in technology, finance, and manufacturing. Having held senior positions at organizations such as Standard Chartered, Hewlett-Packard, and TikTok, he 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.

In “Build a Generative AI LLM-Powered Chatbot to Enhance Customer Service,” Siew Yee guides learners in understanding the practical implementation of AI chatbots to automate communication workflows. His sessions cover prompt engineering, intent classification, and API integration to create dynamic, customer-focused conversational systems. By combining business strategy with AI technology, he equips professionals with the skills to design impactful chatbots that elevate customer experiences.

Truman Ng: 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 Kin Nam: 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.