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

Core topics by TODO:

• Foundations and best practices of information theory and data communication applied to a data project.
• Understanding the different Data Visualization approaches
• Coding for DataViz with D3.js programming paradigm
• Introduction to Vega Framework
• Prototyping effective data visualizations following the design process and best practices of data visualization theory

Guest lectures:

• Data Communication by TOP-IX
• Open Data and DataViz by Sheldon Studio
• Visualizing Data and case studies by Accurat