Artificial intelligence is evolving at a pace that outstrips the regulatory frameworks intended to manage it, leaving organizations to navigate a complex environment where legislation, technical governance, and practical application intersect. The AI Regulation and Compliance course addresses this challenge by converting intricate frameworks into operational, measurable, and practical tools for professionals who utilize AI in their daily work.
Our instructor-led live training courses are aligned with the dynamics of contemporary governance, covering risk classification, transparency obligations, data-handling standards, human oversight requirements, and the evolving responsibilities of deployers, providers, and end users. Participants explore how key regulations such as the EU AI Act, ISO/IEC 42001, NIST AI RMF, and emerging national models influence daily decision-making across procurement, design, and frontline operations.
Online live training sessions utilize an interactive remote desktop environment, providing teams with a secure space to trial documentation workflows, assess compliance scenarios, and practice governance tasks under controlled conditions.
Onsite sessions in Lille, whether held at client premises or NobleProg training centers, bring regulatory concepts into the physical workspace, enabling participants to apply obligations directly to existing processes, industry requirements, and organizational culture.
Also referred to as AI Governance, AI Compliance, or AI Regulatory Readiness, this course track equips professionals to interpret regulatory obligations, mitigate risk exposure, and align their organization's AI usage with the rapidly changing legal landscape.
NobleProg — Your Local Training Provider
Lille, Gare Flandres
NobleProg Lille, 21 Avenue le Corbusier, Lille, france, 59800
In front of Flandres TGV Train Station
From Lille train stations
From Lille-Flandres: the address is essentially right next to the station — about 1–3 minutes on foot.
From Lille-Europe: walk toward Lille-Flandres along Avenue Le Corbusier. It is roughly 5–10 minutes on foot.
So you don't need a bus or metro if you're arriving by train.
If you're coming by bus
The nearest bus stops to Avenue Le Corbusier include Lion d'Or and Jacquet. Several local lines serve the area, including 13, 86, L5 and L91.
This live training in Lille assists intermediate governance, compliance, and risk professionals in developing AI programs that comply with the EU AI Act. The course covers interpreting regulatory duties, creating governance workflows, evaluating risks, and preparing for audits through practical, hands-on exercises.
This instructor-led training in Lille enables managers to comprehend EU AI Act obligations, governance requirements, and strategic implications. Participants will gain the ability to define priorities, establish accountability, communicate risks, and construct governance structures to ensure compliance.
This practical, hands-on training in Lille empowers IT professionals with the engineering controls required for EU AI Act compliance. Participants will learn to architect secure CI/CD pipelines, implement observability, and generate audit-ready evidence, providing teams with actionable, technical strategies for compliance.
This live, instructor-led training in Lille assists novice end users in understanding EU AI Act compliance. The curriculum covers identifying restricted practices, adhering to safe-use policies, effectively reporting incidents, and maintaining simple evidentiary records. Attendees will develop practical skills to manage daily AI interactions in the workplace responsibly.
This instructor-led session on Lille delves into the influence of AI and machine learning on data governance, compliance, and organizational risk. Participants will learn to pinpoint governance challenges, apply DPIAs, and ensure AI deployments align with critical regulatory and ethical frameworks.
This instructor-led, live training in Lille (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.
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 goals turn software / AI engineers into legal engineers — the people 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.
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