Artificial Intelligence - Deep Learning (Seminar) (4-023)

General objective of the training: To provide a clear and comprehensive overview of Deep Learning, its key concepts, fundamental architectures, and practical applications in a professional context. Modality: All modalities (in-person, virtual classroom, and hybrid) are possible. Possible locations: Client premises or Ascent Formation premises, in metropolitan France and the DROM-COM. Maximum number of participants: 40 Targeted SAME level: Awareness (S) Targeted skills: - Identify the basic principles of Deep Learning and its integration into AI projects. - Understand the different architectures of neural networks (CNN, RNN, etc.). - Comprehend the methodologies for convergence and training of neural networks. - Evaluate the strengths and limitations of Deep Learning architectures.

• Understand the fundamental keys of a Machine Learning or Deep Learning approach.
• Master the theoretical and practical foundations of neural network architecture and convergence.
• Know the different fundamental architectures and master their implementations.
• Master methodologies for deploying neural networks, including their strengths and limitations.