Data science lab: process and methods (2019/2020)


This page has hierarchy - Parent page: Teaching

General information

SSD: ING-INF/05
CFI: 8
Professor: Elena Baralis
Teaching assistants:
Tania Cerquitelli (Lessons), Andrea Pasini (Python classes)
Giuseppe Attanasio, Flavio Giobergia (Laboratory sessions)

Announcements

  • 10-10-2019. The text of the exercises for the Python lectures will be made available in our GitHub repository (check the Python/Material section).
  • 29-09-2019. The first Python lesson will be on 04 October 2019. We suggest you to bring your own PC with Python3 and Jupyter installed.
    In the “Python” section you can find instruction for installing the necessary software.

Learning material

img

Data science

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

  • Course introduction (pdf)
  • Introduction to data science (pdf)
  • Data preprocessing (pdf)
  • Association rules (pdf)
img

Python

This section will contain the slides and material of the Python classes.

Material

  • GitHub repository. Here we will publish text and solutions of the exercises solved during Python lectures.
  • GitHub tutorial (pdf)
  • Python installation tutorial (pdf)

Slides

  • Introduction to Python (pdf)
  • Python programming (pdf)
  • Numpy (pdf)

img

Laboratory material

This section will contain all the material for carrying out laboratories.

  • Laboratory 1 (9-10 October 19): pdf
    Solutions: pdf, html
  • Laboratory 2 (16-17 October 19): pdf
    Solutions: pdf, html
  • Laboratory 3 (23-24 October 19): pdf