Data Science and Machine Learning Lab (2025/26)

Data Science and Machine Learning Lab (2025/26)

General Information

SSD: ING-INF/05

CFU: 8

Professor: Flavio Giobergia

Teaching Assistants: Matteo Berta, Claudio Savelli, Lorenzo Vaiani

Exam rules

Exam rules for A.Y. 2025/26 (slides)


Teaching Material

Data science

This section will contain the slides of the data science course.

Python

This section will contain the slides of the data science course.

Other material

  • Python introduction material (from A.Y. 2024/25)
  • Data exploration on the Ames Housing Dataset (ipynb, Kaggle dataset) – [8/10 and 13/10/2025 lectures]

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.

Material

Team organization

Students will be divided into three groups based on course overlaps and surname. Please ensure you attend the correct slot to ensure there is enough space for everyone during the laboratories.

You can use the following rule:

  • If you are a student of Processi Stocastici or Bioquants, or your last name is from “AA” to “HU” or from “NA” to “RZ”Monday, 10:00–13:00, LAIB3B
  • If you are a student of Numerical Optimization, or your last name is from “IA” to “MU” or from “SA” to “ZZ”Tuesday, 08:30–11:30, LAIB2B

Exam simulation results

The results of the exercise submissions are now available here.

Extra resubmission window

For those interested in comparing improvements with your previous attempts, we are granting one additional week to submit updated solutions. After this evaluation phase concludes, we will publish the reference solution and the ground-truth of the test set.

Important for future submissions and exam

To ensure smooth evaluation, please follow these rules:

  • Put all files in your main working folder (no nested/alternate work dirs).
  • Use clear, consistent filenames exactly as requested (mind spelling and case).
  • Use only relative paths in your code and notebooks – no absolute paths (e.g., avoid /home/..., C:\...).