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Course Details
Course Details
What You'll Learn
Topic 1: Overview of Always-On AI Agents and Human-AI Collaboration
Topic 2: Designing and Building a Single Autonomous AI Agent with Hermes
Topic 3: Designing Multi-Agent Teams to Improve Workflow Efficiency
Course Info
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.
Target Age Group: 21-65 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
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
Dr. Alfred Ang builds AI agents for a living, and he is just as committed to making them understandable for people who have never built one. He is a full-stack AI developer and Agentic AI solution architect who designs conversational agents, RAG pipelines and multi-agent systems with n8n, Langflow, Flowise, CrewAI, Microsoft AutoGen, the OpenAI Agents SDK, the Google Gemini Agent SDK and the Claude Agent SDK, and he serves as Managing Director, CIO, CTO and Chief Instructional Designer of Tertiary Infotech Academy Pte Ltd and founder of Tertiary Courses. He is an IBM certified instructor for the AI Practitioners course, a Microsoft Certified AI Engineer Associate (AI-102) and an AWS Certified AI Practitioner, and he holds a PhD in Electrical Engineering from NUS and a Graduate Diploma in Intelligent Robotics Systems from NUS-ISS. His GitHub, with more than 300 public repositories, includes several beginner-friendly agent builds: n8n-ragdemo, a no-code RAG demo in which a browser PDF uploader feeds a vector store and a Telegram AI agent powered by Google Gemini answers questions from the documents; n8n-inventorycontrol, in which a local LLM reads stock levels, flags items below the reorder threshold and reports through Google Sheets and Gmail; n8n-hrportal, a leave portal with human-in-the-loop manager approval and a guarded HR chatbot; and bakerycourses-demo, a course chatbot that deliberately uses context-stuffing instead of RAG. These small, practical builds are the kind of examples he likes to start beginners with.
In Human-AI Collaboration with Always On AI Agents, Dr. Ang uses examples like these to show that an agent is a design pattern, not magic. The course opens with the foundations of AI agents for business: how large language models combine with reasoning, planning, memory and tool use, and why prompt engineering and context engineering decide whether an agent behaves well. Learners then build and integrate business AI agents that retrieve information and interact with everyday systems such as email, spreadsheets and messaging apps, before moving on to intelligent business automation, where agents take on multi-step workflows and hand decisions back to people at the right points. The final topic covers deploying, governing and optimising agents, including monitoring, cost control and responsible use, shaped by his Certificate in AI Ethics and Governance (Senior Professional) from NTU. He often contrasts approaches side by side, for example showing when simply placing a document in the prompt is enough and when a proper retrieval pipeline is worth the extra effort, so beginners learn to choose the simplest design that works. As an ACTA-certified trainer and DACE-certified curriculum developer, he keeps the pace comfortable for non-programmers and builds every concept through guided demonstrations and hands-on exercises, so learners leave with working agents and the confidence to propose agent projects at work. He also introduces the main agent frameworks, explaining the difference between visual builders and code-based SDKs so learners know which suits them. To see the agents he builds, view his GitHub portfolio at https://github.com/alfredang and connect with him on LinkedIn at https://www.linkedin.com/in/angchewhoe/
Dwight Nuwan Fonseka is Head of Data Science at Plano Pte. Ltd. and an ACLP-certified trainer whose expertise covers data analytics, machine learning and AI applications. His technical work includes predictive modelling and deep learning solutions in Python and R, using frameworks such as TensorFlow and Keras, as well as RShiny dashboards. With a professional background in healthcare, finance and customer analytics, he brings an applied perspective to AI that pays attention to 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 Human-AI Collaboration with Always On AI Agents, Dwight uses his machine learning and applied AI background to make AI agents approachable for newcomers. He explains how agents combine large language models with reasoning, planning, memory and tool integration, then guides learners in building and integrating business AI agents and using them for intelligent automation. The final topic covers deploying, governing and optimising agents, where his focus on AI risk helps participants think about oversight and responsible use. Learners leave with a clear foundation in how AI agents work and practical skills to start automating business processes and supporting better decisions.
Truman Ng's interest in intelligent systems goes back to his undergraduate years at NUS, where he designed an AI controller for a DC-DC power converter using fuzzy logic and neural networks for his final year project before graduating in Electrical Engineering in 2002. Since then he has built over 15 years of project experience in database and web design, PLC machinery, data centre design and enterprise networks, and has completed more than 100 IT network projects for banks, hotels and factories. He is the founder of Nexplore (S) Pte Ltd, an ACTA-certified trainer, and holds PMP, Cisco CCNP and Huawei HCIE R&S and HCNA Cloud certifications.
In Human-AI Collaboration with Always On AI Agents, Truman makes agentic AI approachable for newcomers. He explains how AI agents combine large language models with reasoning, planning, memory and tool integration to carry out business tasks while working alongside people. Learners then build and integrate simple business agents, apply them to automate everyday processes, and learn how to deploy, govern and optimise them responsibly. His experience integrating systems for business clients and managing projects to completion keeps the course grounded in practical outcomes, so participants leave with a clear sense of where agents can improve productivity and decision-making.
Ken Yuen is an ACTA-certified adult educator specialising in STEM education, IoT systems and programming, with Python among the languages he teaches. His career includes roles as an instructor, Application Development Engineer, Technical Consultant and Project Manager. As a Technical Consultant at Anson Engineering he developed IoT-based SCADA and temperature monitoring systems for industrial applications, and in his courses he focuses on automation systems and hands-on experimentation. He holds a Bachelor of Electrical and Electronics Engineering from Nanyang Technological University and is a certified Project Management Professional (PMP).
Ken brings his automation and systems background, rather than a dedicated AI research career, to Human-AI Collaboration with Always On AI Agents. His experience designing systems that monitor conditions and trigger actions gives beginners a concrete way to understand how AI agents combine large language models with reasoning, planning, memory and tools. He walks learners through the foundations of AI agents for business, building and integrating agents, intelligent business automation, and deploying, governing and optimising agents. With his patient, step-by-step teaching style, participants build their first working agents and learn to judge where automation genuinely improves productivity and where human oversight should remain.
Terence Ee is an IT leader and independent consultant with more than 25 years of corporate IT experience in technology management, information systems and digital transformation. As Chief Information Officer at the Supreme Court of Singapore and Vice President of Information Systems at Senoko Energy, he led major IT modernisation projects, and since 2017 he has guided SMEs and enterprises in adopting future-ready digital platforms. An ACLP-certified, WSQ-accredited trainer, he has delivered IT training in Singapore and Myanmar and holds a Master of Science in Technology Management. His current areas of focus include project management, information security management and office productivity applications.
For beginners exploring AI agents, Terence offers the perspective of someone who has introduced new technology into organisations from the leadership seat. He explains what AI agents are and where they fit in business, then guides learners through building and integrating simple agents and using them to automate everyday business processes. His IT governance and information security background shapes the final topic on deploying, governing and optimising agents, helping participants think about oversight, risk and continuous improvement from the start. Using case studies and hands-on practice, he makes the subject approachable for non-technical learners, who leave with a working understanding of AI agents and a practical sense of how to apply them responsibly at work.
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