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AI Security and Governance

Sessions 1 day
Duration 7.5 hrs
Level Beginner
Assessment NA

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

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This course is for beginners. No prerequisite is required.

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

AI Security and Governance

Course Code: C1440

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AI Security and Governance equips you to manage the risks that artificial intelligence introduces as it becomes embedded in everyday business systems. Chatbots answering customers, models scoring decisions and AI agents acting on live data all create new exposures, such as prompt injection, data leakage, model manipulation and unintended actions, that traditional security controls were not designed to handle. The course is designed for security, risk and compliance professionals, IT and data leaders, and managers responsible for deploying AI safely.

You will start with the AI risk and threat landscape, understanding how AI systems work, the attack surface they create and key threats catalogued by resources such as the OWASP Top 10 for LLM Applications and MITRE ATLAS. Next you will explore AI governance frameworks and policy, including the NIST AI Risk Management Framework, ISO/IEC 42001, regulatory developments and how to set AI policies, roles, inventories and approval processes. You will then cover securing models, data and agents, applying access controls, data protection, guardrails, monitoring and least-privilege design.

The final topic covers assurance, oversight and response, including testing and red-teaming AI systems, auditing and monitoring for drift and misuse, human oversight and incident response for AI failures. Case studies and practical exercises help you apply each concept to your own organisation. By the end, you will be able to assess AI risks, build a practical governance programme and implement controls that let your organisation adopt AI securely and responsibly.

This course is part of our AI training in Singapore, where you can browse all our AI courses. See more AI security training.

Hands-On Learning Learn by doing. Every topic is practised hands-on, so you leave with skills you can use at work straight away.
Live Coaching Experienced instructors coach you live, answer your questions and guide you step by step.
Free Post-Course Consultation Stuck after class? Message your trainer any time for guidance as you apply what you have learned.
Always-Updated Materials Materials are refreshed to stay relevant. Log in to our LMS any time to get the latest version.

No funding is available for this course

For WSQ funding, please checkout the details at WSQ - AI Security Governance for Businesses

Course Fee

$350.00 (GST-exclusive)

$381.50 (GST-inclusive)

Mode of Training

Physical Classroom Training
Virtual Class by LiVE Instructor
Corporate Training at Company Premise

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Sponsorship

Self-Sponsored
Employer-Sponsored

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Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

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.

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
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: AI Security Governance Foundations and Business Risks

Topic 2: Building an AI Governance Framework: Policies, Roles and Risk Ownership

Topic 3: Governance Controls Across the AI Lifecycle

Topic 4: Security Controls for Agentic AI, Risk Assessment and Implementation Roadmap

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: 18-65 years old

Minimum Software/Hardware Requirement

Software:

You will need the following for this course:

A web browser such as Google Chrome, Microsoft Edge or Safari – free
Access to the course materials provided in class

Hardware: Windows PC or Mac laptop

Trainers

Dr. Alfred Ang teaches AI Security and Governance from the position of someone who designs, deploys and secures AI systems himself. He holds a Certificate in AI Ethics and Governance (Senior Professional) from NTU and is CompTIA Security+ certified, credentials he pairs with his work as a full-stack AI developer and Agentic AI solution architect. As Managing Director, CIO, CTO and Chief Instructional Designer of Tertiary Infotech Academy Pte Ltd, his experience spans system architecture, security and observability for platforms ranging from learning management systems to customer-facing AI chatbots. His wider credentials include Microsoft Certified AI Engineer Associate (AI-102), AWS Certified Solutions Architect, AI Practitioner and Cloud Practitioner, and PMP and ITIL certification, along with a PhD in Electrical Engineering from NUS and experience in the defence, electronics and semiconductor industries. His public GitHub portfolio shows the security habits he teaches: an n8n self-service HR portal whose OpenAI chatbot is protected by input and output guardrails, an accessible IT service desk demo with a credential-leak guard and a strict Content Security Policy, PMO dashboards with hardened CSP, a set of Claude Code skills that includes a secret scanner, and an ERP prototype with signed webhooks and human-in-the-loop approvals. He builds multi-agent systems and RAG pipelines with frameworks such as n8n, the OpenAI Agents SDK, the Claude Agent SDK and Microsoft AutoGen, so he understands exactly where agents can be misled or overreach. He has also worked in the defence, electronics and semiconductor industries, sectors where security and process discipline are taken seriously.

That hands-on knowledge shapes how he runs this course. Learners begin with the AI risk and threat landscape, examining how prompt injection, data leakage, model manipulation and unintended agent actions arise in real systems rather than in theory. He then guides them through building an AI governance framework, defining policies, roles and risk ownership that fit their own organisation, and mapping governance controls across the AI lifecycle from data sourcing and model selection to deployment, monitoring and retirement. The final topic focuses on agentic AI, where he draws on his own agent designs to show how tool permissions, guardrails, approval steps, logging and least-privilege access reduce the blast radius of an autonomous system, before learners assemble a risk assessment and a practical implementation roadmap. He also shows how standards and frameworks can be translated into checklists that engineering, legal and business teams can actually follow, and how to test an AI system the way an attacker would, using simple red-teaming exercises on prompts and tool calls. As an ACTA-certified trainer and DACE-certified curriculum developer, he keeps the material concrete for security, risk and compliance professionals as well as IT and data leaders, using worked scenarios and discussion so that every participant leaves with controls and governance artefacts they can apply immediately. 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/

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 teaches AI from an applied perspective that focuses on both the opportunities and the risks of emerging technologies. His hands-on work includes developing predictive models, deep learning solutions and RShiny dashboards with R, Python, TensorFlow and Keras, and his professional background spans healthcare, finance and customer analytics, where sensitive data must be handled carefully. He also holds a Masters in Education from NTU and has eight years of teaching experience.

In AI Security and Governance, Dwight brings his understanding of how AI models and systems are built to the question of how they should be governed. He covers AI security governance foundations and business risks, building an AI governance framework with clear policies, roles and risk ownership, and governance controls across the AI lifecycle. The final topic addresses security controls for agentic AI, risk assessment and an implementation roadmap. His practitioner view helps learners understand exposures such as prompt injection, data leakage and unintended agent actions, so they leave able to put practical governance and controls in place for AI in their organisation.

Terence Ee's current areas of focus include information security management, quality management and project management, and as a WSQ-accredited trainer he also delivers programmes in IT governance. He brings more than 25 years of corporate IT experience, including senior management roles as Chief Information Officer at the Supreme Court of Singapore and Vice President of Information Systems at Senoko Energy, where he led major IT modernisation projects. Since 2017 he has worked as an independent consultant and ACLP-certified trainer. He holds a Master of Science in Technology Management and a Bachelor of Science in Computer and Information Sciences, and has delivered IT training in Singapore and Myanmar.

In this course, Terence applies his information security and IT governance background to the risks introduced by AI systems. Learners start with the foundations of AI security governance and the business risks involved, then build an AI governance framework covering policies, roles and risk ownership. They go on to apply governance controls across the AI lifecycle and examine security controls for agentic AI, finishing with a risk assessment and an implementation roadmap. Having held CIO-level responsibility in a public institution, he is well placed to show how governance works in practice, not just on paper. Participants leave with a practical framework they can adapt to their own organisation.

Dr Alvin Ang is an ACTA-certified trainer whose interest lies in real-world data science. He holds a PhD, Masters and Bachelors from NTU, Singapore, and has served as a Principal Consultant (Data Science) and an Assistant Professor, in addition to eight years as an adjunct lecturer at SUSS. An operational researcher by study, he favours practical application over theory, and he owns a startup.

AI Security and Governance draws on his data science consulting perspective, since the data and models that power AI systems are where many of the risks begin. Dr Ang guides learners through the foundations of AI security governance and the business risks involved, building an AI governance framework with clear policies, roles and risk ownership, applying governance controls across the AI lifecycle, and assessing security controls for agentic AI before setting out an implementation roadmap. His structured, practical approach helps participants translate principles into concrete actions for their own organisations. Learners leave able to identify where chatbots, decision-scoring models and AI agents create exposure, and to put proportionate controls and clear accountability in place.