Artificial intelligence has revolutionized many fields of science, and is now beginning to revolutionize a large number of economic sectors (industry, medicine, communications, etc.).
Nevertheless, its
presentation in the mainstream media is often nothing more than fantasy. The aim of this training course is to present these approaches and their contribution to solving problems considered to be “intelligent”.

Technical resources

Course material projected during training and sent to all trainees at the end of the course; case studies and practical examples chosen according to trainees' areas of interest

Performance monitoring

All trainees are asked to sign in every half-day Evaluation: Questionnaire to assess skills acquired at the end of the course

Assessment of results

Post-training satisfaction questionnaire

Pedagogical objectives

This course aims to provide participants with a high-level overview of deep learning and its current applications, as well as an understanding of the opportunity and methodology for implementing such projects.

Technologies covered

Tensorflow Serving, Kubernetes, Docker, PyTorch, Caffe. Cloud services: Google Cloud Service, Microsoft Azure, Amazon SageMaker

Target skills

  • Mastery of fundamental neural network concepts and algorithms
  • Deep learning project methodology
  • Master the stages of progress, control and validation of a deep learning project.
  • Industrialization