Core topics by ISI:

• Machine Learning algorithms with Sklearn
• Statistical Learning Theory with practical exercises
• Neural Networks and Backpropagation
• Building from scratch and training neural networks with TensorFlow and Keras
• Brief history of Deep Learning, with focus on Computer Vision
• Building from scratch and training deep convolutional NNs with TensorFlow and Keras
• Transfer Learning: feature extraction and fine-tuning

Guest lectures:

• Machine Learning Explainability by Nexi
• Training Deep Learning Models and HPC4AI by Unito
• Machine Learning in forecasting by Glovo