Course Details
Topic 1 Introduction to Artificial Intelligence (AI)
- What is AI, Machine Learning and Deep Learning?
- Brief History of AI
- Catalog of AI Technologies
- How AI Technologies Can Disrupt Businesses.
Topic 2 Potential Opportunities of AI Innovation
- AI Use Cases in Healthcare Industry
- AI Use Cases in Security Industry
- AI Use Cases in Robotics Industry
- AI Use Cases in Transport Industry
- AI Use Cases in Manufacturing
Topic 3 AI Technologies
- Introduction to Neural Network
- Overview of Computer Vision
- Overview of Natural Language Processing (NLP)
- Overview of Reinforcement Learning
- Overview of Generative Models
Topic 4. AI Adoption
- Challenges of AI Adoption
- Cost-Benefit Analysis of AI Implementation
Topic 5: AI Implementation
- Success Factors of AI Implementation
- Design Thinking Approach to AI Implementation
- The Future Trend of AI
Mode of Assessment
- Written Assessment - Short Answer Questions (WA-SAQ)
- Oral Questioning (OQ)
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 with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
- 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 18 years old
Minimum Software/Hardware Requirement
Software: NIL
Hardware: Windows or Mac Laptops
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 |
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SkillsFuture Credit:
PSEA:
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Absentee Payroll (AP) Funding:
SFEC:
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Steps to Apply Skills Future Claim
- The staff will send you an invoice with the fee breakdown.
- Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
- Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
- Upload your invoice and click ‘Submit’
SkillsFuture Level-Up Program
The SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme
Get Additional Course Fee Support Up to $500 under UTAP
The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).
For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)
Steps to Apply UTAP
- Log in to your U Portal account to submit your UTAP application upon completion of the course.
Note
- SSG subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
- All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
- An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
- UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
- UTAP support amount will be paid to training provider first and claimed after end of class by learner.
Appeal Process
- The candidate has the right to disagree with the assessment decision made by the assessor.
- When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
- If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
- If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
- If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
- 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.
- The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
- The candidate must lodge the appeal within 7 days, giving reasons for appeal
- The assessor can help the candidate with writing and lodging the appeal.
- he assessment manager will collect information from the candidate & assessor and give a final decision.
- A record of the appeal and any subsequent actions and findings will be made.
- An Assessment Appeal Panel will be formed to review and give a decision.
- The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
- The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
- Please click the link below to fill up the Candidates Appeal Form.
Job Roles
- Innovation Manager
- Business Strategist
- AI Product Manager
- Data Scientist
- Business Intelligence Analyst
- Digital Transformation Specialist
- R&D Specialist
- AI Solutions Architect
- Chief Technology Officer (CTO)
- Marketing Innovation Specialist
- Operations Manager (with AI focus)
- Startup Founder (AI-driven ventures)
- IT Project Manager (AI integrations)
- Customer Experience Strategist
- Supply Chain Innovation Manager
Trainers
Tan Woei Ming: 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.
In “Business Innovation with Artificial Intelligence,” Woei Ming guides participants in leveraging AI as a strategic tool for driving business transformation and competitive advantage. His sessions explore real-world use cases of AI in product development, customer engagement, and operational efficiency, focusing on practical frameworks for innovation. By combining technical depth with a business-centric approach, he helps learners understand how to harness AI technologies to generate new value, improve decision-making, and create sustainable growth in a rapidly evolving digital economy.
Dwight Nuwan Fonseka: Dwight Nuwan Fonseka is an ACLP-certified trainer and Head of Data Science at Plano Pte. Ltd., where he develops AI-driven predictive analytics, R Shiny dashboards, and deep learning models for healthcare solutions. He also lectures at the London School of Business and Finance (LSBF), coordinating the Diploma in Data Analytics, and serves as an associate trainer with Tertiary Courses. His expertise includes R, Python, Keras, and h2oAI, as well as cloud platforms such as AWS for big data analytics and machine learning deployment.
In his AI innovation training, Dwight emphasizes practical applications of machine learning and AI to transform business processes. He equips learners with the ability to design, implement, and evaluate AI solutions, focusing on areas such as text mining, time series forecasting, and image recognition. By combining his strong academic and industry background, Dwight ensures participants understand not only the theory of AI but also how to apply it strategically for business innovation.
Dr Alvin Ang: Dr Alvin Ang is an ACLP-certified trainer with a Ph.D. in Operations Research from Nanyang Technological University and over a decade of academic and industry experience. He has taught data science, AI, and machine learning at NTU, SUSS, Curtin University, and SP Jain School of Global Management, as well as serving as an IBM Data Science Instructor. As founder of DataFrens.sg, he also fosters open-source collaboration in AI and data science across Singapore.
In his training, Dr Ang focuses on helping learners apply AI to drive business innovation and problem-solving. His sessions cover supervised and unsupervised learning, deep learning with TensorFlow, and practical case studies that show how AI can enhance efficiency and create new business opportunities. With his structured, hands-on approach, Dr Ang enables participants to develop both technical skills and strategic insight in leveraging AI for business growth.
Terence Ee: Terence Ee is an independent consultant and trainer with over 25 years of experience in IT management, enterprise systems, and digital transformation. He has held leadership positions including Chief Information Officer at the Supreme Court of Singapore and Vice President of Information Systems at Senoko Energy, where he implemented large-scale IT innovation and digital strategy projects. Holding a B.Sc. in Computer and Information Sciences from NUS and an M.Sc. in Technology Management from Staffordshire University, Terence bridges executive-level strategy with technical expertise.
In his AI innovation training, Terence emphasizes the organizational adoption of AI to improve decision-making, optimize processes, and create new value streams. He guides learners in understanding AI fundamentals, business applications, and change management considerations. By integrating real-world executive experience with applied AI knowledge, he equips participants to confidently lead AI-driven innovation in their organizations.
Quah Chee Yong: Quah Chee Yong is an ACLP-certified trainer and experienced data science professional specializing in AI, NLP, and machine learning. He has served as Data Science Training Lead at MSITEK, delivering AI programs under SAP, Temasek Polytechnic, and IMDA, and as AI Solutions Lead at AiDeal Scan, where he developed recommender systems and NLP-driven search engines. He also headed the data science team at GoWild Singapore, building analytics platforms and chatbot applications powered by machine learning.
Quah’s AI innovation training focuses on making advanced AI concepts accessible and practical for business users. His sessions cover recommender systems, customer analytics, and chatbot integration, showing participants how AI can directly enhance customer experience and business growth. By combining technical expertise with strong teaching experience, he ensures learners gain the knowledge and confidence to apply AI strategically for business innovation.
Customer Reviews (137)
- will recommend Review by Course Participant/Trainee
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. (Posted on 5/8/2024)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 - will recommend Review by Course Participant/Trainee
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The desk were quite dirty and the power plugs seems to be overloaded. (Posted on 5/8/2024)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 5/8/2024)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 5/8/2024)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 5/8/2024)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 - will recommend Review by Course Participant/Trainee
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Excellent! Would love to attend training conducted by Terence. (Posted on 5/8/2024)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 5/8/2024)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 - might recommend Review by Course Participant/Trainee
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Was expecting a tea break and lunch but was disappointed. (Posted on 5/8/2024)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 4/28/2024)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 4/27/2024)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 - will recommend Review by Course Participant/Trainee
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Refill 3 in 1 coffee more frequently (Posted on 2/28/2024)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 - All are good Review by Course Participant/Trainee
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All are good (Posted on 2/28/2024)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 2/6/2024)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 - will recommend Review by Course Participant/Trainee
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So far so good (Posted on 12/15/2023)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 - Alfred has been knowledgeable Review by Course Participant/Trainee
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Good work from Lectuerer. (Posted on 11/14/2023)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 - Great session! Review by Course Participant/Trainee
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All good so far, appreciate the use of apps and tools which doesn’t require payments or account creations. (Posted on 10/10/2023)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 6/12/2023)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 5/27/2023)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 - will recommend Review by Course Participant/Trainee
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Not sure of how to improve it because this course already provides me an in-depth knowledge of AI. (Posted on 4/30/2023)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 - will recommend Review by Course Participant/Trainee
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. (Posted on 4/30/2023)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








