Introduction and basic concepts
Frequent itemset, sequence mining, and information retrieval
Dimensionality reduction and data decomposition
Regression, regularization, and optimization
Neural networks and deep learning
Self-supervised neural networks
Deep learning models and applications (text, vision, and audio)
Making lighter neural networks and machine learning models
Challenges of working with data.
