AI Regulation and Compliance Training in Dartmouth

The EU AI Act is a comprehensive regulatory framework that establishes obligations for organisations building, deploying, or overseeing AI systems.

This instructor-led, live training (online or onsite) is aimed at intermediate-level governance, compliance, and risk professionals who wish to build, evaluate, and maintain AI governance programs aligned with the EU AI Act.

Following completion of this course, participants will be able to:

• Interpret regulatory obligations and map them to internal controls.
• Develop documentation, governance mechanisms, and compliance workflows.
• Assess AI risks, monitor systems, and perform ongoing compliance checks.
• Prepare the organisation for internal and external audits under the EU AI Act.

Format of the Course

• Regulatory briefings with real-world examples.
• Hands-on exercises in mapping controls and drafting compliance documents.
• Workshop-style activities for risk analysis and audit preparation.

Course Customization Options

• This course can be adapted to the organisation’s sector, regulatory exposure, and AI maturity level.

The EU AI Act is a regulatory framework designed to ensure trustworthy, safe, and transparent deployment of AI systems.

This instructor-led, live training (online or onsite) is aimed at beginner-level and intermediate-level managers who wish to understand organisational obligations, governance expectations, and strategic implications of aligning with the EU AI Act.

Upon completion of this course, participants will be able to:

• Interpret the EU AI Act’s requirements in a management context.
• Define strategic priorities and investment areas to support compliance.
• Establish governance structures, accountability lines, and oversight mechanisms.
• Communicate obligations, risks, and expectations across business units.

Format of the Course

• Instructor-led presentations supported by case studies.
• Group discussions and scenario-based decision-making activities.
• Practical exercises focused on governance planning and documentation.

Course Customization Options

• The curriculum can be adapted to your organisation’s sector, maturity level, and governance model.

This course is a technical, hands-on programme that shows how to implement engineering controls, observability, and automation required to meet the EU AI Act compliance obligations.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT professionals who wish to implement secure, auditable pipelines and runtime safeguards to demonstrate compliance with Article 4 and related obligations.

After completing this training, participants will be able to:

• Design CI/CD pipelines that incorporate governance checks and automated tests for prohibited practices.
• Implement logging, monitoring, and audit trails to produce compliance evidence.
• Apply technical mitigations for high-risk behaviours and configure runtime safeguards.
• Prepare technical documentation and artifacts required for conformity assessments and audits.

Format of the Course

• Technical lectures with architecture diagrams and demonstrations.
• Hands-on labs building CI/CD pipelines and monitoring stacks.
• Practical exercises producing documentation and audit artifacts.

Course Customization Options

• Content can be tailored to your organisation’s toolchain, cloud provider, and internal compliance workflows.

The EU AI Act is a regulatory framework that sets rules for the development, deployment, and use of AI systems within the EU and for services offered to EU users.

This instructor-led, live training (online or onsite) is aimed at beginner-level end users who wish to understand their obligations and safe practices under the EU AI Act.

Upon completion of this training, participants will be able to:

• Identify prohibited AI practices under Article 4 and recognise examples in workplace systems.
• Follow organisational policies and safe-use procedures when interacting with AI systems.
• Report incidents, biases, or unexpected model behaviour through the correct channels.
• Document simple compliance evidence required by supervisors or auditors.

Format of the Course

• Interactive presentations with plain-language explanations of legal requirements.
• Role-specific exercises and realistic workplace scenarios.
• Guided practice in reporting incidents and completing simple compliance checklists.

Course Customization Options

• Content can be tailored to reflect your organisation’s AI inventory, policies, and reporting channels.

AI and Machine Learning are rapidly evolving technologies with significant implications for data governance and organizational compliance.

This instructor-led, live training (online or onsite) is aimed at intermediate-level governance, privacy, and compliance professionals who wish to understand how to implement robust information governance practices in environments using AI and machine learning.

By the end of this training, participants will be able to:

• Understand the core concepts of AI and machine learning in an information governance context.
• Identify typical areas where AI/ML is deployed in organizations and related IG risks.
• Evaluate how AI/ML interacts with Data Protection Principles, records management, and data quality.
• Apply DPIAs, governance frameworks, and risk mitigation approaches to AI/ML projects.

Format of the Course

• Interactive lecture and discussion.
• Real-world case examples and framework analysis.
• Group activities and guided document walkthroughs.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level AI professionals, business leaders, and compliance officers who wish to understand and implement ethical practices in AI systems. The course covers key ethical frameworks, regulatory standards like the EU AI Act, and practical techniques for auditing AI systems to mitigate bias and enhance transparency.

By the end of this training, participants will be able to:

• Understand core principles of responsible AI, including fairness, accountability, and transparency.
• Identify and mitigate biases within AI systems.
• Implement ethical frameworks and conduct AI audits for compliance.
• Apply governance strategies to manage ethical risks in AI deployment.

Delegates will learn how to

• AIGP training teaches how to develop, integrate, and deploy trustworthy AI systems in line 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 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.
• Presents awareness of unforeseen concerns with AI and knowledge of debated issues surrounding AI governance.
• This training teaches 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.