AI Fundamentals
This "AI Fundamentals" Master Class offers a structured immersion into the world of Artificial Intelligence. Far from the hype, this training aims to provide a clear and pragmatic understanding of current technologies, from historical concepts to the recent revolutions of Generative AI (GenAI). Through concrete examples and situational exercises, participants will learn to distinguish the different types of AI, identify value drivers for the business (notably via the "Augmented Collaborator" concept), and master the crucial challenges of responsibility (AI Act, ethics, bias). Finally, the course integrates an essential dimension of digital sobriety, analyzing the environmental impact of AI to encourage sustainable innovation.
Ce que vous allez apprendre
- Master the fundamentals and vocabulary of AI (Machine Learning, Deep Learning, GenAI, LLM, Prompt, RAG) and understand the structure of the current ecosystem.
- Identify the potential of AI in business by distinguishing traditional use cases from new generative opportunities, and understanding the strategic role of a GenAI platform.
- Adopt a responsible posture towards ethical and regulatory risks by understanding the requirements of the European AI Act and the mechanisms of algorithmic bias.
- Integrate digital sobriety issues into the use of technologies by knowing the environmental impact of the AI life cycle.
Prérequis
- No prior technical skills are required (neither in development nor in data science). A curiosity for digital issues and innovation is recommended.
- A laptop with an internet connection for demonstrations and access to online resources.
- Access to internal collaboration tools (Teams/Google Meet) if the session is held remotely.
Public cible
- All employees, regardless of their profession or hierarchical level (technical, functional, support, managers)
Programme de la Formation
6 modules pour maîtriser les fondamentaux
Sujets abordés
- →Welcome and presentation of objectives.
- →Round table: expectations and sharing of representations of AI (myths vs. reality).
Quality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
- Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Prochaines sessions
Aucune date ne vous convient ?
Nous organisons régulièrement de nouvelles sessions. Contactez-nous pour connaître les prochaines dates disponibles ou pour organiser une session à la date de votre choix.
S'inscrire à une date personnaliséeFormer plusieurs collaborateurs
- Tarifs dégressifs (plusieurs places)
- Session privée ou sur-mesure
- En présentiel ou à distance