Data Analytics for Digital Health (DAD) - 9 CFU A.Y. 2025/2026

Instructors:

Anna Monreale
- KDDLab, Università di Pisa
- anna [dot] monreale [at] unipi [dot] it
Francesca Naretto
- KDDLab, Università di Pisa
- francesca [dot] naretto [at] unipi [dot] it

News

[08.09.2025] Lecture of the first week will be canceled, so they will start on 22nd September 2025

Learning Goals

Fundamental concepts of data knowledge and discovery.
Data Types in Healthcare Data and Public Databases
Data understanding
Data preparation
Clustering
Classification
Rule-based methods
Outlier Detection
Time Series Analysis
Sequential Pattern Mining

Hours and Rooms

Classes

Day of Week	Hour	Room
Monday	09:00 - 11:00	Room FIB PS4
Tuesday	14:00 - 16:00	Room C
Friday	11:00 - 13:00	Room FIB PS4

Office hours - Ricevimento: Anna Monreale: TBD - Online using Teams or in my Office (Appointment by email). Francesca Naretto: TBD - Online using Teams or in my Office (Appointment by email).

A Teams Channel will be used ONLY to post news, Q&A, and other stuff related to the course. The lectures will be only in presence and will NOT be live-streamed.

Learning Material -- Materiale didattico

Textbook -- Libro di Testo

Pang-Ning Tan, Michael Steinbach, Vipin Kumar. Introduction to Data Mining. Addison Wesley, ISBN 0-321-32136-7, 2006
- http://www-users.cs.umn.edu/~kumar/dmbook/index.php
- Chapters 4,6 and 8 are also available at the publisher's Web site.
Jake VanderPlas. Python Data Science Handbook: Essential Tools for Working with Data. 1st Edition.
For Python Notions: Very basic notions on Python

Slides

The slides used in the course will be inserted in the calendar after each class. Most of them are part of the slides provided by the textbook's authors Slides per "Introduction to Data Mining".

Software

Python - Anaconda (at least 3.7 version!!!): Anaconda is the leading open data science platform powered by Python. Download page (the following libraries are already included)
Scikit-learn: python library with tools for data mining and data analysis Documentation page
Pandas: pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Documentation page

Class Calendar (2025/2026)

First Semester

	Day	Topic	Learning material	References	Teacher
1.	22.09	Overview. Introduction to Data Analyics for DH + Data Types		Chap. 1 Kumar Book	Monreale

Exams

TBD

Previous years

Data Analytics for Digital Health (DAD) - 9 CFU A.Y. 2024/2025