Responsible AI and AI Ethics Training Course

This instructor-led training in Latvia examines the intersection of AI, Machine Learning, and organizational data governance. Learners will explore how to navigate compliance challenges, execute DPIAs, and align AI initiatives with essential regulatory and ethical standards.

Upon completion, participants will be equipped to:

• Apply enterprise-grade prompt architecture across six key 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 involved teams.
• Establish sustainable governance structures, including defining the Prompt Curator role, naming conventions, versioning protocols, and quality metrics.
• Conclude with tangible outputs: a v1.0 Prompt Library, a Governance Charter, and a 30-Day Deployment Plan.

Assessment format for participants

• Interactive workshops designed for multiple roles (Architects, Developers, QA, and Team Leaders).
• Guided co-creation facilitated by an architect-consultant, allowing participants to build functional, real-world deliverables.
• All co-created assets remain the sole property of the client organization.

Customization options for the course

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

This instructor-led live training in Latvia provides a guided introduction to EU AI Act compliance for end users at an introductory level. It covers the identification of prohibited practices, adherence to safe-use policies, effective incident reporting, and basic evidence documentation. Participants will develop practical skills for navigating daily workplace interactions with AI.

This live training in Latvia empowers intermediate governance, compliance, and risk professionals to develop 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 exercises.

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

This instructor-led training in Latvia assists managers in comprehending their EU AI Act obligations, governance requirements, and strategic impacts. Participants will gain the skills to define priorities, establish clear accountability structures, communicate risks effectively, and build robust governance frameworks for compliance.

Participants will learn to

• The AIGP training guides you on how to develop, integrate, and deploy trustworthy AI systems in compliance with evolving laws and policies. The curriculum offers an overview of AI technology, a review of current legislation, and strategies for risk management, security and safety, privacy protection, and related topics.
• Establish foundational knowledge of AI systems and their use cases, the impacts of AI, and comprehension of responsible AI principles.
• Demonstrate an understanding of how current and emerging laws apply to AI systems, and how major frameworks are capable of being responsibly governed.
• Show comprehension of the AI life cycle, 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.
• This training covers critical AI governance concepts that are also integral to the AIGP certification exam. While not purely a “test prep” course, this training is suitable for professionals who intend to certify, as well as for those seeking 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 building AI for legal tasks like eDiscovery, review, and investigations.

In two days, participants will build the full core stack: ingesting and extracting complex real-world legal data, enabling search and retrieval, implementing retrieval-augmented generation (RAG) with citations, ensuring privacy via local models, executing defensible AI reviews with court-ready metrics, and packaging the solution for deployment.