
About Course
Artificial Intelligence (AI) / Machine Learning (ML) is fast becoming a crucial part of business processes and is touted to be the key to successful digital transformation.
However, these phrases remain buzzwords to many business executives. Without a basic understanding of AI/ML, the participation of these key personnel will be limited, and such digital transformations may fall short.
This 2-day course is for business/non-technical managers or executives, and it seeks to introduce and demystify these machine learning concepts.
The objective of this course is to equip business managers and executives with the foresight and relevant technical grounding to transform their businesses digitally.
Who Should Attend
Prerequisites
- Basic computer literacy and no advance preparation is required
Learning Outcomes
The Evolution of AI: From Rules to Generative Intelligence
- Participants will explore how AI has evolved from rule-based systems to machine learning, deep learning and generative AI
- They will examine key milestones in AI, such as AlphaGo, GPT, DALL·E, etc.
- Participants will understand why recent advances in data, computing power, and model architectures have accelerated AI progress
How Most AI Works: Neural Networks Made Simple
- Participants will learn how Neural Networks (NNs) function as layered decision-makers
- They will understand how models are trained using data to make predictions
- Real-world applications of basic NNs will be illustrated
- Hands-on activity will demonstrate the difference between training and inference using web-based tools
Machines That See: Convolutional Neural Networks
- Participants will be introduced to Convolutional Neural Networks (CNNs), a modern NN architecture to model static patterns
- Use cases such as medical imaging, surveillance, autonomous vehicles will be explored
- Hands-on activity allows participants to visualise CNNs with web-based tools
Generative AI: Transformers
- Participants will learn how transformers (a modern NN architecture) model temporal patterns
- They will understand how key components like embedding and attention mechanisms work
- Generative use cases across text, image, and multimodal generation will be explored
- Hands-on comparisons of outputs from tools like ChatGPT, Gemini and Grok will be included
AI in Practice: Developing AI Software
- Participants will understand the AI development lifecycle from data preparation to modelling, deployment, evaluation and iteration
- The importance of high-quality data in model collection and preparation will be emphasised
- Participants will be introduced to the basics of model evaluation metrics such as the confusion matrix, precision and recall
The AI Economy and Its Impact on Work and Society
- Participants will explore how AI is reshaping industries, including finance, education and healthcare
- They will understand the difference between job transformation and job replacement
- National strategies and investments in AI from countries like Singapore, the United States and China will be discussed
- Participants will recognise AI literacy as an essential skill for career competitiveness

Prompting for Results: Human-AI Interaction
- Participants will learn the fundamentals of prompting in AI and why it‘s critical for performance
- They will practise effective prompting techniques such as role prompting, task prompting and step-by-step reasoning
- Common prompting pitfalls and debugging strategies for poor AI responses will be explored
- Advanced prompting methods such as few-shot, chain-of-thought and system messages will be introduced
Hands-On Workshop: Applying AI to Real Use Cases
- Participants will apply their AI knowledge to solve specific domain challenges relevant to their work
- They will engage in peer sharing and a discussion session
Introduction to Agentic AI and Autonomous Tools
- Participants will be introduced to Agentic AI and how it differs from chatbots
- Examples of AI agents and copilots such as AutoGPT and Microsoft Copilot will be shared
- Use cases including automated research, workflow orchestration and customer support will be covered
- Participants will explore the future of AI that can plan, reason, and act with autonomy
Teaching Team

Soh Cheng Lock, Donny
Associate Professor / Prog Leader, Infocomm Technology, Singapore Institute of Technology

Tan Chek Tien
Associate Professor, Infocomm Technology, Singapore Institute of Technology
Course Details
Schedule
Course Run | Dates | Time |
---|---|---|
July 2025 Run | 17 – 18 Jul | 9:00 am – 6:00 pm |
October 2025 Run | 30 – 31 Oct | 9:00 am – 6:00 pm |
Day 1
Topics |
---|
Introduction to Artificial Intelligence, Machine Learning, Supervised Learning / Unsupervised Learning / Reinforcement Learning, and Computer Vision Case Study 1: AI in Manufacturing |
Day 2
Topics |
---|
Recap Introduction to Neural Networks, and Natural Language Processing Case Study 2: AI in Business Support Case Study 3: AI in Finance |
Certificate and Assessment
A Certificate of Attainment will be issued to participants who:
- Attend at least 75% of the course
- Undertake and pass non-credit bearing assessment during the course
Participants who meet the attendance requirement but do not pass the assessment will receive a Certificate of Participation.
Fee Structure
The full fee for this course is S$1,744.00.
Funding Category | Eligible Funding | Course Fees Payable After Funding |
---|---|---|
Singapore Citizen (Below 40) | 70% | S$523.20 |
Singapore Citizen (40 & Above) | 90% | S$203.20 |
Singapore PR / LTVP+ Holder | 70% | S$523.20 |
Non-Singapore Citizen | Not Eligible | S$1,744.00 |
Note: All fees above include GST. GST applies to individuals and Singapore-registered companies.
Course Runs
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