Data Science And Machine Learning Lab – prof. Flavio Giobergia

• Copies of the slides used during the lectures, examples of written exams and exercises, and manuals for the activities in the laboratory will be made available. All teaching material is available on the course website.

Argomenti del programma: • Data science process: main phases (0.4 cfu) • Data collection, cleaning, transformation and enrichment, and feature engineering (0.5 cfu) • Data mining algorithms: classification, regression, clustering, association rule mining, anomaly detection (1.8 cfu) • Introduction to data mining and machine learning libraries in Python (e.g., scikit-learn) (1.2 cfu) • Case study analysis (0.6 cfu) • Data science process…