Responsible AI and AI Ethics Training Course

This instructor-led training in Thailand delves into the influence of AI and machine learning on data governance, compliance, and organizational risk. It equips participants to pinpoint governance hurdles, execute DPIAs, and ensure AI deployments adhere to essential regulatory and ethical standards.

Upon completion, participants will be able to:

• Master enterprise prompt architecture across six layers: Role, Context, Constraints, Domain Standards, Format, and Examples.
• Integrate business, security, and compliance requirements (including GDPR, EU AI Act, and sector-specific standards) directly into prompts.
• Collaboratively build a prompt library that is validated, shared, and governed across all teams.
• Establish sustainable governance structures, including the Prompt Curator role, naming conventions, versioning, and quality metrics.
• Conclude with tangible outcomes: Library v1.0, Governance Charter, and a 30-Day Deployment Plan.

Course format and assessment approach

• Interactive workshops designed for multiple profiles (Architects, Developers, QA, Team Leaders).
• Guided co-construction led by an architect-consultant, enabling participants to create real-world, operational deliverables.
• All co-created deliverables become the exclusive property of the client organization.

Customization options

• To request a tailored version of this training, please contact us to discuss the necessary arrangements.

This instructor-led, live training in Thailand assists beginner end users in achieving EU AI Act compliance. It covers identifying prohibited practices, adhering to safe-use policies, effectively reporting incidents, and documenting essential evidence. Participants will develop practical skills for managing daily workplace AI interactions.

This live training in Thailand is designed to assist intermediate-level governance, compliance, and risk professionals in developing AI programs that meet EU AI Act standards. The course covers interpreting regulatory obligations, building governance workflows, assessing risks, and preparing for audits through hands-on practical exercises.

This hands-on training in Thailand empowers IT professionals with the engineering controls essential for EU AI Act compliance. Learn to design secure CI/CD pipelines, implement observability, and generate audit-ready evidence. Ideal for teams seeking practical, technical compliance strategies.

This instructor-led training in Thailand assists managers in understanding their obligations under the EU AI Act, including governance and strategic implications. Participants will learn to define priorities, establish accountability lines, communicate risks, and build robust governance structures for compliance.

Participants will learn how to

• Develop, integrate, and deploy trustworthy AI systems in accordance with emerging laws and policies. The curriculum provides an overview of AI technology, a survey of current law, and strategies for risk management, security and safety considerations, privacy protection, and other topics.
• Establish foundational knowledge of AI systems and their use cases, the impacts of AI, and an understanding of responsible AI principles.
• Demonstrate an understanding of how current and emerging laws apply to AI systems, and how major frameworks can be responsibly governed.
• Show comprehension of the AI life cycle, the context in which AI risks are managed, and the implementation of responsible AI governance.
• Gain awareness of unforeseen concerns with AI and knowledge of debated issues surrounding AI governance.
• Learn critical AI governance concepts that are also integral to the AIGP certification exam. While not purely a "test prep" course, this training is appropriate for professionals who plan to certify, as well as for those who want to deepen their AI governance knowledge. Both the training and the exam are based on the same body of knowledge.

Course goals: transform software and AI engineers into legal engineers—professionals who can effectively build AI for legal tasks such as eDiscovery, review, and investigations.

In two days, participants will construct the full core stack: ingesting and extracting messy real-world legal data, searching and retrieving information, implementing retrieval-augmented generation (RAG) with citations, maintaining privacy using local models with proof, executing defensible AI reviews with court-ready metrics, and packaging the result for deployment.