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WSQ - Business Innovation with Artificial Intelligence

WSQ - Business Innovation with Artificial Intelligence

Elevate your business operations and strategy through the transformative power of artificial intelligence with this WSQ-endorsed course. Our curriculum covers how AI can be applied to various facets of your business, from automating mundane tasks to leveraging data analytics for strategic decisions. You'll get hands-on experience through practical exercises and learn from real-world case studies, ensuring that your newfound knowledge is readily applicable.

By completing this course, you'll be well-equipped to integrate artificial intelligence into your business model. You'll understand the types of AI technology that are most relevant to your industry and learn how to implement them to solve complex problems, increase efficiency, and drive innovation. Whether you're a corporate executive, business owner, or a professional looking to upskill, this course provides you with the tools and insights to innovate effectively with AI.

Learning Outcomes

By the end of the course, learners will be able to

LO1: Compare current business model with artificial intelligence business model
LO2: Explore potential opportunities for using artificial intelligence
LO3: Identify various types of artificial intelligence technologies
LO4: Weigh the costs-benefits of adopting artificial intelligence
LO5: Implement business innovation processes with artificial intelligence

Course Brochure

Download WSQ - Business Innovation with Artificial Intelligence Brochure

Skills Framework

This course follows the guideline of Business Innovation ICT-SNA-4003-1.1 TSC under ICT Skills Framework

Certification

Certificate of Completion from Tertiary Infotech - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Infotech.
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 Funding

WSQ funding is only applicable to Singaporeans and PR. Subject to eligibility, the funding support is subjected to funding caps.

Effective for courses starting from 1 Jan 2024
Full Fee	GST	Nett Fee after Funding (Incl. GST)
		Baseline	MCES / SME
$350	$31.50	$206.50	$136.50

Baseline: Singaporean/PR age 21 and above
MCES(Mid-Career Enhanced Subsidy): S'porean age 40 & above

Upon registration, we will advise further on how to tap on the WSQ Training Subsidy.

You can pay the nett fee (after the WSQ training subsidy) by the following :

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover of 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

Course Code: TGS-2020504518

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.

Course Cancellation/Reschedule Policy

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
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

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

Singapore Citizens or Singapore Permanent Residents of age 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

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

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.