(SCTP) AI Accelerator Programme

Learners will build a structured foundation in AI — covering machine learning, deep learning, large language models, generative AI, and agentic systems. The focus is on business relevance: how AI creates value, where it carries risk, and how to evaluate AI outputs critically and responsibly.

This course brings together the disciplines of data-driven decision-making and data storytelling, empowering learners to harness the full potential of Generative AI across the entire analytics lifecycle — from raw data to impactful narrative.

This course provides a structured, end-to-end learning journey — from understanding how a single AI assistant is built, to analysing how multiple agents collaborate to solve complex enterprise problems.

This course provides a practical exploration of the AI risk landscape, covering international regulation, enterprise risk management implications, and the emerging role of RiskTech solutions. Over two days, participants will examine how AI, automation, and machine learning systems work in practice, where their risk exposures arise, and how those risks manifest in real organisational settings, illustrated through case studies. The programme explores how AI risks are governed across the three lines of defence, drawing on leading frameworks including the Monetary Authority of Singapore (MAS) Fairness, Ethics, Accountability, and Transparency (FEAT) Principles and the National Institute of Standards and Technology (NIST) AI Risk Management Framework, alongside established approaches to model risk, operational risk, and technology governance. Participants will also review the growing toolkit of AI control and assurance practices, including monitoring, validation, documentation, and emerging RiskTech solutions that support responsible and auditable AI deployment.

This course provides an executive briefing on the current landscape of AI tools and solutions. It begins with a plain-language overview of how modern AI systems work, what they can and cannot do, and where they are creating real organisational value. The course then focuses on the role of leadership in guiding AI adoption across the full lifecycle, from Discover and Design through Deliver and De-Risk. Participants will examine how leading organisations structure AI operating models, manage governance and accountability, and balance innovation with risk control. Leaders will leave with a clear understanding of the practical capabilities of AI, machine learning, and automation; common success and failure patterns in AI initiatives; how AI programmes are structured and governed; and how regulatory expectations are evolving.

This course equips professionals with applied-strategic knowledge required to adopt, implement, and realise measurable value from Artificial Intelligence (AI) initiatives within Singapore enterprise environments.

Participants will examine AI adoption maturity models, implementation lifecycle frameworks, organisational readiness factors, stakeholder alignment strategies, and value realisation methodologies. The course contextualises AI adoption within Singapore’s enterprise landscape, including regulatory expectations, public sector digitalisation initiatives, and private sector competitiveness priorities.

This course equips professionals with applied technical knowledge to understand how AI solutions are built, hosted, and scaled in cloud computing environments.

Participants will examine cloud service models, AI workload deployment patterns, scalability considerations, cost management principles, and reliability factors in enterprise AI systems.

This course requires participants to apply the full spectrum of knowledge acquired throughout the AI Accelerator Programme to design and propose an end-to-end AI-enabled solution for an enterprise problem.

Participants may select from pre-curated Singapore enterprise problem statements or propose a real workplace problem.

DIVE FURTHER bridges theory and practice, empowering participants to apply Design·AI methodologies to real business challenges.

Over two intensive days, you’ll learn to identify high-impact opportunities and prototype AI-enhanced solutions for measurable business outcomes.

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The Certified Generative AI Professional training offers professionals an opportunity to expand their existing skills and acquire the expertise needed to excel in the evolving landscape of AI. Through practical exercises and interactive discussions, this course ensures you will be well-prepared to integrate AI into your work and drive technological advancements.

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The Certified Prompt Engineering training is an opportunity for professionals to focus on enhancing your existing skills and be equipped with the expertise needed to navigate the exciting field of GenAI Prompt Engineering. Through hands-on activities and interactive discussions, this course ensures you will be well-prepared to integrate AI into your work or explore its possibilities.

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This course equips professionals with applied skills to design, build, and orchestrate autonomous AI agents for workplace use cases. Learners will progress from foundational understanding of agentic systems to the practical creation of goal-oriented AI workflows using zero-code and low-code approaches.

The course focuses on enabling learners to move beyond static prompting towards agent-driven task execution, workflow automation, and responsible deployment of AI agents within organisational contexts, while addressing governance, safety, and human-in-the-loop considerations.

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This course equips professionals with the applied skills required to effectively integrate Generative AI capabilities into everyday workplace tasks using Microsoft Copilot within the Microsoft 365 ecosystem. Learners will develop practical competence in using Copilot to enhance productivity, improve collaboration, analyse data, automate workflows, and generate business-ready content while adhering to organisational security, governance, and ethical requirements.

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• In-class participation
• Individual assessment
• Group work