Deep learning & artificial intelligence : an introduction

Lecturer(s): Emmanuel DELLANDREA, Alberto BOSIO, Alexandre SAIDI, Céline HARTWEG-HELBERT, Liming CHEN
Course ⋅ 16 hStudy ⋅ 12 h


By making possible breakthroughs supposed to be impossible until recently in a growing number of domains, e.g., computer vision, natural language processing, autonomous driving or games, deep learning has revolutionized the artificial intelligence domain that has become one of the major pillars of our society. In this course, our goal is to introduce the basis of concepts and technics in deep learning

Palabras clave

Deep learning, artificial intelligence, supervised learning, reinforcement learning, PyTorch


  • Introduction to machine learning and deep learning
  • Classification/regression and gradient descent
  • Computational graphs & backpropagation
  • Training deep neural networks
  • Convolutional Neural Networks (CNN)
  • CNN Architectures
  • Deep reinforcement learning (Actor, Critic, Actor-Critic)
  • Embedded Deep Learning

Learning Outcomes

  • Understanding the principles of deep learning
  • Mastering fundamental techniques for supervised learning and reinforcement learning
  • Being able to deploy a deep learning approach with the PyTorch framework


50% written exam, 50% evaluation of the assignments