Artificial Intelligence and Machine Learning: How to Implement Good Information Governance Training Course

This instructor-led live training (online or onsite) is designed for intermediate-level AI professionals, business leaders, and compliance officers who aim to understand and implement ethical practices in AI systems. The course covers essential ethical frameworks, regulatory standards such as 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.

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

• Master enterprise prompt architecture across 6 layers (Role, Context, Constraints, Domain Standards, Format, Examples).
• Encode business, security, and compliance constraints (GDPR, EU AI Act, sector standards) directly into prompts.
• Co-build a prompt library that is validated, shared, and governed by all teams.
• Define sustainable governance: Prompt Curator role, naming conventions, versioning, quality metrics.
• Leave with concrete deliverables: Library v1.0, Governance Charter, 30-Day Deployment Plan.

Course format for participant assessment

• Interactive multi-profile workshops (Architects, Developers, QA, Team Leaders).
• Facilitated co-construction by an architect-consultant: participants build real, operational deliverables.
• All co-built deliverables belong entirely to the client organization.

Course customization options

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

The EU AI Act establishes a regulatory framework governing the development, deployment, and use of artificial intelligence systems within the EU, as well as for services provided to EU-based users.

This instructor-led live training, available online or on-site, is designed for beginner-level end users who want to understand their obligations and adhere to safe practices under the EU AI Act.

Upon completing this training, participants will be able to:

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

Course Format

• 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 organization’s AI inventory, policies, and reporting channels.

The EU AI Act establishes a comprehensive regulatory framework that defines the obligations for organizations developing, deploying, or overseeing artificial intelligence systems.

This instructor-led live training, available both online and onsite, is designed for intermediate-level professionals in governance, compliance, and risk management who aim to build, evaluate, and sustain AI governance programs that align with the EU AI Act.

Upon completing this course, participants will be able to:

• Interpret regulatory requirements and align them with internal controls.
• Create necessary documentation, establish governance structures, and implement compliance workflows.
• Evaluate AI-related risks, monitor systems, and conduct ongoing compliance checks.
• Prepare the organization for both internal and external audits required under the EU AI Act.

Course Format

• Regulatory briefings supported by real-world examples.
• Practical exercises focused on mapping controls and drafting compliance documentation.
• Workshop-style activities designed for risk analysis and preparing for audits.

Customization Options

• The course content can be tailored to fit your organization’s specific sector, regulatory exposure, and current AI maturity level.

This technical, hands-on programme demonstrates how to implement the engineering controls, observability, and automation necessary to fulfill EU AI Act compliance obligations.

Designed as an instructor-led, live training session (available online or onsite), this course targets intermediate-level IT professionals seeking to establish secure, auditable pipelines and runtime safeguards that demonstrate adherence to Article 4 and related requirements.

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

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

Format of the Course

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

Course Customization Options

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

The EU AI Act establishes a robust regulatory framework aimed at fostering the trustworthy, secure, and transparent deployment of artificial intelligence systems.

This instructor-led training session, available either online or onsite, is designed for beginner to intermediate-level managers seeking to grasp their organisation’s obligations, governance expectations, and the strategic impact of aligning with the EU AI Act.

After completing this course, participants will be equipped to:

• Analyze the EU AI Act’s requirements within a managerial framework.
• Identify strategic priorities and investment areas necessary for compliance.
• Implement governance structures, define accountability chains, and establish oversight mechanisms.
• Effectively communicate obligations, risks, and expectations across various business units.

Course Format

• Instructor-led presentations enriched with real-world case studies.
• Group discussions and scenario-based decision-making exercises.
• Practical workshops focused on governance planning and documentation.

Customization Options

• The curriculum can be tailored to suit your organisation’s industry sector, maturity level, and existing governance model.

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.

Course objectives transform software / AI engineers into legal engineers — professionals who can actually build AI for legal work (eDiscovery, review, investigations).

In two days, participants build the full core stack: ingest and extract messy real-world legal data, search and retrieve it, add retrieval-augmented generation (RAG) with citations, keep it private on a local model and prove it, run a defensible AI review with court-ready metrics, and package the result for deployment.