Responsible AI and AI Ethics Training Course

This instructor-led training in Denmark examines the impact of AI and machine learning on data governance, compliance, and organizational risk. Learners will gain the skills to identify governance challenges, apply DPIAs, and effectively align AI deployments with key regulatory and ethical frameworks.

By the end of this training, 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 by all teams.
• Establish sustainable governance structures, including the Prompt Curator role, naming conventions, versioning, and quality metrics.
• Depart with tangible deliverables: Library v1.0, a Governance Charter, and a 30-Day Deployment Plan.

Course format for participant assessment

• Interactive multi-profile workshops involving Architects, Developers, QA, and Team Leaders.
• Facilitated co-construction led by an architect-consultant, enabling participants to create real, operational deliverables.
• All co-built deliverables remain the exclusive property of the client organization.

Course customization options

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

This instructor-led live training in Denmark walks beginner end users through the essentials of EU AI Act compliance. Participants will learn to spot prohibited practices, adhere to safe-use policies, manage incident reporting, and gather basic evidence. The course builds practical competencies for everyday workplace interactions with AI.

This live training in Denmark supports intermediate professionals in governance, compliance, and risk management as they build AI programmes aligned with the EU AI Act. The course covers interpreting obligations, developing governance workflows, assessing risks, and preparing for audits through hands-on exercises.

This practical training in Denmark equips IT specialists with the necessary engineering controls to ensure EU AI Act compliance. It focuses on designing secure CI/CD pipelines, implementing robust observability, and generating evidence ready for audits. It is ideal for teams seeking practical, technical strategies for compliance.

This instructor-led training in Denmark empowers managers to navigate EU AI Act obligations, governance requirements, and strategic implications. Participants will develop the ability to set priorities, establish clear accountability, communicate risks effectively, and build robust governance structures for compliance.

Participants will learn how to

• Through AIGP training, learn how to develop, integrate, and deploy trustworthy AI systems in compliance with emerging laws and policies. The curriculum covers an overview of AI technology, a survey of current laws, and strategies for risk management, security and safety considerations, privacy protection, and other relevant topics.
• Build foundational knowledge of AI systems and their use cases, the impacts of AI, and an understanding of responsible AI principles.
• Demonstrate understanding of how current and emerging laws apply to AI systems, and how major frameworks can be responsibly governed.
• Show comprehension of the AI lifecycle, the context in which AI risks are managed, and the implementation of responsible AI governance.
• Present awareness of unforeseen concerns with AI and knowledge of debated issues surrounding AI governance.
• Acquire 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 objectives transform software and AI engineers into legal engineers—professionals capable of constructing AI systems for legal workflows (eDiscovery, review, investigations).

Within two days, participants will build a complete core stack: ingesting and extracting complex real-world legal data, performing search and retrieval, implementing retrieval-augmented generation (RAG) with citations, maintaining privacy using local models with verifiable proof, executing defensible AI reviews with court-acceptable metrics, and packaging the solution for deployment.