Data Science and Machine Learning Lab (2026/27)

General Information

SSD: ING-INF/05

CFU: 8

Professor: Flavio Giobergia

Teaching Assistants: Matteo Berta, Claudio Savelli, Lorenzo Vaiani

Exam rules

The exam rules for A.Y. 2026/27 will be published here.

---

Teaching Material

Data science

This section contains the theory slides for the DSML course.

• Course introduction (slides)
• Introduction to data science & machine learning (slides)
• Data preprocessing (slides)
• Classification fundamentals (slides)
• Regression analysis (slides)
• Introduction to Deep Learning (slides)
• Association rules (slides)
• Clustering fundamentals (slides)
• Anomaly Detection (slides) (PDF notebook) (.ipynb notebook)

Python

This section contains the Python slides for the DSML course.

• NumPy (slides)
• Pandas (slides)
• Matplotlib (slides)
• Scikit-learn (Classification) (slides)
• Scikit-learn (Regression) (slides)
• Scikit-learn (Pre-processing) (slides)
• Scikit-learn (Clustering) (slides)
• PyTorch (slides)

Exercises

Other material

• Python introduction material (from A.Y. 2024/25)
  • Introduction to Python (slides)
  • Python programming (slides)
  • Structuring Python projects (slides)
  • Lab “0”: Python basics (text, solution)
  • Scientific writing (slides)

---

Laboratory Material

This section will contain all the material for carrying out laboratories. No laboratory will be evaluated and assigned a mark, so no laboratory will give additional points to the final exam.