• Objectifs :
  – Acquérir une vision globale de l’IA et de son évolution historique.
  – Découvrir les différents types d’IA et leurs applications concrètes.
• Contenu :
  – Définition de l’IA : Qu’est-ce que l’intelligence artificielle ?
  – Types d’IA : IA faible vs IA forte, IA supervisée vs non supervisée.
  – Applications concrètes : Exemples d’utilisation de l’IA dans les secteurs d’activité des stagiaires (Commerce, santé, finance, industrie, etc.).
• Méthodes pédagogiques :
  – Présentation théorique : Support visuel (slides) avec exemples concrets.
  – Quiz interactif sur DIGIFORMA  pour évaluer les connaissances initiales.
  – Échanges en direct : Questions-réponses pour clarifier les concepts.
• Outils utilisés :
  – Plateforme de visioconférence (Zoom).
  – Outil de quiz interactif sur DIGIFORMA.

• Objectifs :
  Identifier les technologies clés de l’IA (Machine Learning, Deep Learning, Réseaux de neurones).
  – Expérimenter l’utilisation d’un outil d’IA générative.
• Contenu :
  Machine Learning : Principes de base et applications.
  – Deep Learning : Fonctionnement des réseaux de neurones.
  – Outils d’IA générative : Présentation de ChatGPT, DALL-E, et autres outils populaires.
  – Démonstration en direct : Utilisation d’un outil d’IA générative pour résoudre un problème concret.
• Méthodes pédagogiques :
  – Atelier pratique : Manipulation d’un outil d’IA générative en petits groupes.
  – Démonstration en temps réel : Utilisation de ChatGPT pour générer du contenu.
  – Questions-réponses : Interaction avec le formateur pour approfondir les concepts.
• Outils utilisés :
  – Outil d’IA générative (ChatGPT, DALL-E).
  – Plateforme de visioconférence avec partage d’écran.

• Objectifs :
  – Découvrir les applications concrètes de l’IA dans différents secteurs.
  – Analyser des études de cas pour comprendre l’impact de l’IA.
• Contenu :
  – Optimisation et personnalisation : Comment l’IA améliore les processus métiers.
  – Analyse prédictive : Utilisation de l’IA pour anticiper les tendances.
  – Études de cas : Exemples concrets dans les secteurs de la santé, de la finance et de l’industrie.
• Méthodes pédagogiques :
  – Travaux en sous-groupes : Analyse d’études de cas en petits groupes.
  – Restitution en plénière : Partage des résultats et feedback du formateur.
  – Débats : Échanges sur les bénéfices et les limites de l’IA dans chaque secteur.
• Outils utilisés :
  – Plateforme de visioconférence avec salles de sous-commission (breakout rooms).
  – Tableau blanc collaboratif Mural pour organiser les idées.

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• Objectifs :
  – Prendre conscience des enjeux éthiques et réglementaires liés à l’IA.
  – Débattre sur des scénarios éthiques pour développer une réflexion critique.
• Contenu :
  – Biais algorithmiques : Comment les biais peuvent influencer les décisions de l’IA.
  – Protection des données : Enjeux de confidentialité et de transparence.
  – Réglementations en vigueur : RGPD, AI Act, et autres lois pertinentes.
• Méthodes pédagogiques :
  – Débats en groupe : Discussion sur des scénarios éthiques.
  – Sondages en direct : Recueil des opinions des participants via SurveyMonkey.
  – Études de cas : Analyse de situations réelles pour comprendre les implications éthiques.
• Outils utilisés :
  – Outil de sondage en ligne SurveyMonkey.
  – Plateforme de visioconférence.