Artificial intelligence is evolving at a pace that outstrips the regulatory frameworks intended to oversee it, compelling organizations to navigate a complex environment where legislation, technical governance, and practical application intersect. AI Regulation and Compliance enters this arena by converting intricate frameworks into operational, measurable, and practical strategies for the teams utilizing AI daily.
Our instructor-led live training programs mirror the dynamics of contemporary governance, addressing risk classification, transparency duties, data-handling norms, human oversight requirements, and the evolving responsibilities of deployers, providers, and end-users. Participants analyze how regulations such as the EU AI Act, ISO/IEC 42001, NIST AI RMF, and emerging national models influence daily operations, spanning from procurement and design to frontline implementation.
These concepts are delivered via online live training through an interactive remote desktop, providing teams with the opportunity to test documentation workflows, assess compliance scenarios, and practice governance tasks in a controlled setting.
In-person sessions in Athens, conducted either at client sites or NobleProg training centers, integrate regulatory concepts into the physical workspace. This approach enables participants to align obligations with existing processes, sector-specific requirements, and organizational culture.
Recognized as AI Governance, AI Compliance, or AI Regulatory Readiness, this course track equips professionals to interpret obligations, mitigate risk exposure, and align organizational AI usage with the rapidly changing legal environment.
Take Metro Line 3 (M3) from Airport toward Dimotiko Theatro.
Get off at Evangelismos.
The address is on Vasilissis Sofias Avenue, very close to the station. Evangelismos station is directly on the avenue.
Allow roughly 40–50 minutes total, depending on waiting/walking time.
From Athens Central Railway Station (Larissa Station)
Take the metro to Syntagma and change to Line 3 toward Doukissis Plakentias/Airport.
Get off at Evangelismos.
Walk to No. 46.
By bus
There are several buses running along Vasilissis Sofias Avenue. Nearby stops include Rigilis Street and Syntagma, while the Evangelismos area is served by multiple bus routes.
The metro is generally the simplest option, especially if you're arriving with luggage.
This live training in Athens supports mid-level governance, compliance, and risk experts in constructing AI programs that meet EU AI Act standards. It encompasses interpreting regulatory duties, creating governance workflows, evaluating risks, and preparing for audits through hands-on practice.
This instructor-led training in Athens empowers managers to grasp EU AI Act obligations, governance requirements, and strategic implications. Participants will learn to define priorities, establish accountability lines, communicate risks, and build robust governance structures for compliance.
This hands-on training in Athens equips IT professionals with the engineering controls required for EU AI Act compliance. Learn to design secure CI/CD pipelines, implement observability, and generate audit-ready evidence. Ideal for teams seeking practical, technical compliance strategies.
This instructor-led live training in Athens guides beginner end users through EU AI Act compliance. Participants learn to identify prohibited practices, adhere to safe-use policies, effectively report incidents, and document essential evidence. Attendees will acquire practical skills for managing daily workplace interactions with AI.
This instructor-led course on Athens examines the impact of AI and Machine Learning on data governance, compliance, and organizational risk. Learners will master identifying governance challenges, executing DPIAs, and ensuring AI deployments align with critical regulatory and ethical standards.
This instructor-led, live training in Athens (online or on-site) is designed for intermediate-level AI professionals, business leaders, and compliance officers seeking 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.
Upon completion of this training, participants will be able to:
Grasp the fundamental principles of responsible AI, encompassing fairness, accountability, and transparency.
Detect and address biases present in AI systems.
Deploy ethical frameworks and perform AI audits to ensure compliance.
Utilize governance strategies to manage ethical risks associated with AI deployment.
Utilize AIGP training to develop, integrate, and deploy trustworthy AI systems in alignment 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 key 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.
Apply critical AI governance concepts that are integral to the AIGP certification exam. While this training is not solely a 'test prep' course, it is appropriate for professionals planning to certify, as well as those wishing 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 work (eDiscovery, review, investigations).
Over two days, participants construct the full core stack: ingesting and extracting messy real-world legal data, searching and retrieving it, implementing retrieval-augmented generation (RAG) with citations, ensuring privacy via local models, executing defensible AI reviews with court-ready metrics, and packaging the result for deployment.
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