You have no items in your shopping cart.
Course Details
Course Details
What You'll Learn
Topic 1: Evolution of Business AI from Generative AI to Autonomous AI Agents
Topic 2: Generative AI, Agentic AI and AI Agent Technologies
Topic 3: Context, Harness and Loop Engineering for AI Agents
Topic 4: Business Opportunities and Innovative Agentic AI Use Cases
Topic 5: Evaluating and Implementing AI-Driven Business Innovation
Assessment
- Written Exam
- Oral Questioning
Course Info
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:
You will need the following for this course:
- A free account on a generative AI assistant of your choice, e.g. ChatGPT, Google Gemini or Microsoft Copilot (the free tier is sufficient)
Hardware: Windows PC or Mac laptop
Funding Eligibility Criteria
Self-sponsored learners (individuals)
- Singapore Citizens and Singapore Permanent Residents aged 21 and above.
- Up to 50% course fee funding. Singapore Citizens aged 40 and above receive up to 70% under the Mid-career Enhanced Subsidy (MCES).
- Singapore Citizens aged 25 and above can pay the remaining fee with SkillsFuture Credit.
Company-sponsored learners
- Singapore Citizens and Singapore Permanent Residents who are direct employees of the sponsoring company.
- Up to 50% course fee funding, or up to 70% for employees of SMEs (Enhanced Training Support for SMEs) and for Singapore Citizens aged 40 and above. An SME has no more than 200 employees or an annual turnover of no more than $100 million.
- Employers can also claim Absentee Payroll funding for employees who attend during working hours.
- Eligible companies can offset their out-of-pocket fees with SkillsFuture Enterprise Credit (SFEC).
Conditions for all funded learners
- Attendance is taken digitally with Singpass for every session, including the assessment.
- You must complete the course and pass all assessments (assessed as Competent).
- If these conditions are not met, the funding is clawed back and the learner or employer pays the full course fee.
- 9% GST is charged on the full course fee before funding.
- Promo and discount codes cannot be used on funded courses.
- Any balance after funding can be paid in cash, with SkillsFuture Credit, or partly reimbursed by UTAP for NTUC members.
How to Apply SkillsFuture Credit Claim for Individuals
Singapore Citizens aged 25 and above can use their SkillsFuture Credit (base tier) to pay the course fee after funding. The $4,000 mid-career top-up cannot be used for this course.
- Register for this course as self-sponsored and tell us you will use SkillsFuture Credit. Do not pay the amount you plan to claim.
- We email you an invoice showing the course fee after funding.
- From 60 days before the course starts, and no later than the course start date, log in to MySkillsFuture with Singpass and click Claim credits.
- Click Submit a Claim and search for this course by its course code, TGS-2026064716.
- Select your class start date, enter the course fee payable after funding and the amount of credit to claim, then upload the invoice (PDF, JPG or PNG, under 4MB).
- Review, accept the terms and click Agree and Submit. The credit is paid directly to us; processing can take up to 14 working days.
Changing or withdrawing: cancel the claim on MySkillsFuture at least one day before the course starts. If your class date changes, cancel the claim and submit a new one with the new date.
How to Apply SkillsFuture Enterprise Credit (SFEC)
SFEC helps companies pay for employee training. The current SFEC ends on 30 November 2026, and a redesigned SFEC starts on 1 December 2026.
Current SFEC: classes ending on or before 30 November 2026
- Eligible companies received a one-off $10,000 credit, notified by letter to their Corppass administrator. Eligibility generally required at least 3 Singapore Citizen or PR employees and Skills Development Levy contributions.
- SFEC covers up to 90% of the company's out-of-pocket course fee after other subsidies.
- Check your company's SFEC eligibility and balance on EnterpriseSG.
- Register your Singapore Citizen or PR employee for a class that ends by 30 November 2026, as company-sponsored, and pay the course fee after funding.
- Your employee attends and completes the course. We submit the attendance and assessment results to SWDA.
- No separate claim is needed. SFEC is calculated automatically once the course fee grant is approved and is paid quarterly to your company's IRAS GIRO or PayNow Corporate account.
Any unused balance of the current SFEC expires on 30 November 2026.
Redesigned SFEC from 1 December 2026
Companies with at least 3 resident employees receive a fresh $10,000 in an online SFEC wallet that offsets out-of-pocket fees upfront at enrolment, instead of reimbursing them afterwards. SWDA has not yet published the support rates and claim steps; see OurWorkforce or our SFEC guide.
How to Apply UTAP (NTUC Members)
NTUC members can claim 50% of the unfunded course fee under the Union Training Assistance Programme (UTAP), capped at $250 a year (aged below 40) or $500 a year (aged 40 and above). The cap is shared with UTAP claims for AI tool subscriptions.
Eligibility: you must be an NTUC member paying full membership fees, with your membership paid up before and during the course and when you claim. The course must not be fully paid for by your employer or another source.
- Make sure your NTUC membership is paid up before the course starts.
- Register for this course with us and pay the course fee after funding and SkillsFuture Credit.
- Attend at least 75% of the course and sit all assessments.
- Within 6 months after the course ends, go to the NTUC U Portal, open UTAP under E-services, log in with Singpass and choose Course Fee Claim.
- Enter the nett course fee you paid (after all subsidies and SkillsFuture Credit, including GST), and upload your invoice or receipt and your certificate or result slip (PDF, JPG or PNG, up to 5MB each).
- NTUC usually pays the claim within 4 weeks of submission.
Read more in our UTAP guide.
Appeal Process
If you disagree with an assessment decision, you have the right to appeal.
- When the assessor gives you feedback, say whether you agree with the outcome. If you agree, you and the assessor sign the Assessment Summary Record; if you disagree, do not sign it.
- Discuss the decision with the assessor or the assessment manager first.
- If you are still not satisfied, tell the assessor you intend to appeal. The assessor records this in the feedback section of the Assessment Summary Record and informs the assessment manager.
- Lodge your appeal within 7 days, giving your reasons, using the Candidate Appeal Form. The assessor can help you write and lodge it.
- An Assessment Appeal Panel reviews the information from you and the assessor and makes a decision. A record of the appeal and its outcome is kept.
- You will be told the outcome within 2 weeks of lodging the appeal. The panel's decision is final.
Job Roles
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
Trainers
As a serial entrepreneur who now architects autonomous AI agents, Dr. Alfred Ang approaches CASL Business Innovation with Artificial Intelligence from both sides of the innovation question: what the technology can do, and what a business should do with it. He founded Tertiary Infotech Pte Ltd in 2012 and transformed it into the Tertiary Courses training platform in 2014, founded Tertiary Robotics in 2015 and established Tertiary Courses Malaysia, and today serves as Managing Director, CIO, CTO and Chief Instructional Designer of Tertiary Infotech Academy Pte Ltd. He is a full-stack AI developer and Agentic AI solution architect who designs multi-agent systems with the Claude Agent SDK, the OpenAI Agents SDK, the Google Gemini Agent SDK, Microsoft AutoGen, CrewAI, n8n, Langflow and Flowise. His public GitHub portfolio reflects the shift from generative AI to agents: AI-powered content management systems built on the Claude Agent SDK with an auto-blog scheduler and a self-improving chatbot; a WSQ courseware generation platform built with the Claude Agent SDK that automates assessment plans and learner guides; a web app that prepares WSQ and CASL course proposals using Claude Code; a set of Claude Code skills that package repeatable tasks for an agent; and an automated video production pipeline in which an agent researches, scripts and renders videos. His qualifications include a PhD in Electrical Engineering from NUS, an online MBA from Universitas 21 Global, a Certificate in AI Ethics and Governance (Senior Professional) from NTU and an Advanced Certificate in Integrating Sustainability for a Future Ready Business from SMU.
In this course he traces how business AI has evolved from generative AI and prompt engineering to agentic AI and AI-powered digital workers, and what that means for business models, operating processes and customer experiences. Learners examine generative AI, agentic AI and AI agent technologies, including reasoning, memory, tool use, skills, workflow execution and human-AI collaboration. The topic on context, harness and loop engineering is where his daily agent-building experience is most valuable: he explains how giving an agent the right context, wrapping it in a well-designed harness of tools, permissions and checks, and running it in a loop that plans, acts, observes and corrects itself makes the difference between an impressive demo and a dependable digital worker, illustrating each idea with patterns from his own Claude Agent SDK projects and skills. Participants then explore business opportunities and innovative agentic AI use cases across functions, and finish by evaluating and implementing AI-driven business innovation, weighing value, cost, risk, governance and change management, informed by his MBA training, his AI governance certification and his experience as a founder. As an ACTA-certified trainer, DACE-certified curriculum developer and the IBM certified instructor for the AI Practitioners course, he balances strategic discussion with live demonstrations, so business leaders and professionals leave with a clear, evaluated innovation idea for their own organisation. Learners who want to see his work for themselves are welcome to browse his GitHub portfolio at https://github.com/alfredang and connect with him on LinkedIn at https://www.linkedin.com/in/angchewhoe/
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. He has led AI initiatives in predictive analytics, automation and process optimisation across the semiconductor and manufacturing industries. He holds 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. His expertise lies in translating complex AI technologies into practical business applications, enabling organisations to innovate through data insights and intelligent automation.
In CASL - Business Innovation with Artificial Intelligence, Woei Ming guides participants in using AI as a strategic tool for business transformation. Learners trace the evolution of business AI from generative AI to autonomous agents, examine generative AI, agentic AI and agent technologies, and explore context, harness and loop engineering for agents. They then identify business opportunities and innovative agentic AI use cases, and evaluate and implement AI-driven innovation. By combining technical depth with a business-centric approach, he helps learners understand what these technologies can realistically deliver, so they can make better decisions about where AI creates new value and sustainable growth.
Dwight Nuwan Fonseka is Head of Data Science at Plano Pte. Ltd. and an ACLP-certified trainer with deep expertise in data analytics, machine learning and AI applications. He has hands-on experience developing predictive models, deep learning solutions and RShiny dashboards using R, Python, TensorFlow and Keras, and a professional background spanning healthcare, finance and customer analytics. Dwight is known for an applied perspective on AI that focuses on both the opportunities and the risks of emerging technologies. He also holds a Masters in Education from NTU and has eight years of teaching experience in international schools.
In CASL Business Innovation with Artificial Intelligence, Dwight applies his data science and cross-industry experience to the business side of AI. He traces the evolution of business AI from generative AI to autonomous AI agents, explains generative AI, agentic AI and AI agent technologies, and introduces context, harness and loop engineering for agents. Learners then explore business opportunities and innovative agentic AI use cases, and evaluate and plan AI-driven innovation. His balanced view of AI's opportunities and risks helps participants separate realistic use cases from hype and build a practical, well-reasoned case for AI innovation in their own organisations.
Quah Chee Yong is an ACLP-certified trainer and data science professional specialising in AI, natural language processing and machine learning. He has served as Data Science Training Lead at MSITEK, delivering AI programmes for 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.
In CASL Business Innovation with Artificial Intelligence, he focuses on making advanced AI concepts accessible and practical for business users. Learners trace the evolution of business AI from generative AI and prompt engineering to agentic AI and autonomous agents, examine the underlying technologies, and explore context, harness and loop engineering for AI agents. They then identify business opportunities and innovative agentic AI use cases, and learn to evaluate and implement AI-driven innovation. His experience delivering recommender systems, customer analytics and chatbot applications provides concrete examples of AI improving customer experience, helping participants apply AI strategically in their own organisations.
Dr Alvin Ang is an ACLP-certified trainer with a PhD 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, and has served as an IBM Data Science Instructor. As founder of DataFrens.sg, he fosters open-source collaboration in AI and data science across Singapore, and his training focuses on helping learners apply AI to drive business innovation and problem-solving.
CASL Business Innovation with Artificial Intelligence suits this business-facing focus well. Learners trace the evolution of business AI from generative AI to autonomous AI agents, examine generative AI, agentic AI and AI agent technologies, and learn the context, harness and loop engineering that make agents dependable. They then explore business opportunities and innovative agentic AI use cases, and evaluate and implement AI-driven business innovation. Dr Ang uses practical case studies to show how AI can improve efficiency and create new business opportunities. His structured, hands-on approach helps participants develop both the technical understanding and the strategic insight to leverage AI for business growth.
Review
Customer Reviews (140)
- will recommend Review by Course Participant/Trainee
-
. (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
-
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
-
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
-
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
-
. (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
Write Your Own Review
- Recommended Courses
- Related Courses
WSQ - Data Mining and Machine Learning Fundamentals for Beginners
$750.00 (GST-exclusive)
$817.50
(GST-inclusive)
CASL - Pattern Recognition and Machine Learning with R
$750.00 (GST-exclusive)
$817.50
(GST-inclusive)
