Course Description
Artificial intelligence is reshaping every sector, every profession, and every organisation — not as a future possibility, but as a present reality. In the UK and France, national AI strategies, regulatory frameworks like the EU AI Act, and significant public and private investment are accelerating deployment across healthcare, finance, manufacturing, government, and beyond. Professionals who do not understand AI cannot lead effectively in the environments it is already transforming.
This course was designed for business leaders, managers, public sector professionals, and employees across all functions who want to develop a genuine, working understanding of artificial intelligence — without needing to become engineers. You will learn how AI systems are built and trained, how they are applied across major industries, what the EU AI Act and UK regulatory frameworks require, how to identify algorithmic bias and fairness risks, and how to contribute to responsible AI governance in your organisation.
Across five progressive modules, you will move from AI foundations and data architecture to sector applications, governance and regulation, and the strategic frontiers of generative AI, human-AI collaboration, and workforce transformation. By the end of this course, you will be equipped to engage with AI confidently — as a leader, a decision-maker, a policy contributor, or an informed professional in a world where understanding AI is no longer optional.
Why Compliance Training Matters
The EU AI Act is now in force — and it creates direct obligations for any organisation that deploys, develops, or procures AI systems in Europe.
From prohibited AI practices to high-risk system obligations and transparency requirements, the regulatory landscape has fundamentally changed. Organisations whose leadership does not understand AI cannot assess these risks, govern these systems, or protect their employees, customers, and legal standing from the consequences of getting it wrong.
Where This Course Takes You
Understand how AI works and speak about it with confidence in any professional context
You will understand the core concepts behind machine learning, neural networks, and generative AI — without needing a technical background — and be able to engage credibly with AI decisions, vendor claims, project proposals, and strategic conversations in your organisation.
Recognise how AI is already transforming your sector and what it means for your role
From healthcare diagnostics and financial risk analytics to smart manufacturing and public services, you will see how AI is being deployed across major industries in the UK and France — and develop the sector-specific awareness to identify where it is creating value, disruption, and risk in your own environment.
Navigate AI governance, regulation, and ethical responsibility with authority
You will understand the EU AI Act and UK regulatory frameworks, identify algorithmic bias and fairness risks, apply GDPR and data protection principles to AI systems, and contribute meaningfully to responsible AI governance — whether your role is operational, strategic, or oversight-focused.
Engage with the future of AI — strategically, critically, and with informed confidence
You will understand the trajectory of generative AI and foundation models, assess the real impact of AI on workforce transformation and reskilling, and engage with the emerging governance and innovation challenges that will define how AI develops in France, the UK, and globally over the coming decade.
Certification
Course Curriculum
5 sections2.5 Hours total length
Module 1 : Fondements de l’intelligence artificielle et de la transformation numérique
- 1.1 Concepts fondamentaux de l’intelligence artificielle et des systèmes intelligents
- 1.2 Évolution historique de la recherche en intelligence artificielle au Royaume-Uni et en France
- 1.3 Disciplines clés de l’IA : apprentissage automatique, réseaux de neurones et science des données
- 1.4 Principes d’une IA responsable : éthique et fondements sociétaux
Module 2 : Architecture des données, algorithmes et développement des systèmes d’IA
- 2.1 Acquisition des données, qualité des données et ingénierie des jeux de données
- 2.2 Algorithmes d’apprentissage automatique, entraînement et évaluation des modèles
- 2.3 Traitement automatique du langage naturel, vision par ordinateur et intelligence vocale
- 2.4 Infrastructures de l’IA : plateformes cloud, calcul haute performance et modèles fondamentaux
Module 3 : Intégration de l’IA dans les secteurs économiques et publics
- 3.1 Intelligence artificielle dans la santé, les biotechnologies et la recherche clinique
- 3.2 Applications de l’IA dans la finance, l’analyse des risques et la prévention de la fraude
- 3.3 Fabrication intelligente, industrie 4.0 et systèmes logistiques autonomes
- 3.4 Intelligence artificielle dans l’administration publique, les services publics et les villes intelligentes
Module 4 : Gouvernance, réglementation et déploiement responsable de l’IA
- 4.1 Protection des données, gouvernance de la vie privée et conformité au RGPD
- 4.2 Biais algorithmiques, équité, explicabilité et transparence
- 4.3 Gestion des risques liés à l’IA, sécurité et cadres d’IA de confiance
- 4.4 Stratégies nationales en matière d’IA, cadres réglementaires et alignement des politiques au Royaume-Uni et en France
Module 5 : Stratégie avancée en IA, innovation et impact sociétal futur
- 5.1 IA générative, modèles fondamentaux et intelligence multimodale
- 5.2 Collaboration humain-IA, intelligence décisionnelle et travail augmenté
- 5.3 Transformation économique, reconversion des compétences et écosystèmes de talents en IA
- 5.4 Nouvelles frontières de l’IA : systèmes autonomes, gouvernance de l’IA et tendances mondiales de l’innovation