Institute for Artificial Intelligence


This one-week bootcamp will teach participants to devise machine learning solutions for visual data problems using deep neural networks. It will provide an introductory overview of the game-changing findings in the literature and how they led artificial intelligence to play an increasingly important role in our daily lives.

Preparatory Material

Bootcamp outline

  • Day #1: Introduction to neural networks
    • Linear layers
    • Activation functions
    • Loss functions
    • Backpropagation & stochastic gradient descent
    • Regularization (keep weights small)
    • Training & testing best practices
  • Day #2: Autoencoders
    • Input reconstruction
    • Dimensionality reduction
    • Unsupervised learning
    • Neural network initialization
  • Day #3: Deep convolutional neural networks
    • Convolutional layers
    • Pooling layers
    • Applications in classification
    • Going deeper (more layers) with residual learning
    • Pre-trained architectures & transfer learning
  • Day #4: Deepfake generation
    • Face preprocessing (detection and normalization)
    • Face autoencoder
    • The one-encoder, two-decoders trick
    • Ethics behind deepfakes
  • Day #5: Deepfake detection
    • Real vs. fake classification
    • Adversarial training and the vicious circularity