98061 - Extracting and mining data from complex sources

Learning outcomes

At the end of the course, the students will understand the main functions of data analytics in data pipelines, such as classification, regression, clustering and the discovery of associative rules; they will have an intuitive knowledge of the application of such functions to available data according to the business goals, and they will understand the importance of a quantitative evaluation of their effectiveness.

Course contents

The general objective of acquiring theoretical knowledge and practical skills about integration and mining of data will be pursued by developing three areas:

• understand the main functions of data analytics and data mining in the context of "data-driven decisions", such as classification, regression, clustering and discovery of association rules;
• understand how to apply the above functions to the available data, focusing to the possible "business objectives; understand the importance of a quantitative evaluation of effectiveness
• learn to develop simple elaborations of data for assisting data-driven decisions, using a tool with graphical user interface.

Readings/Bibliography

Course Slides and online reading material provided during classes

Teaching methods

Classes in presence and laboratory practice

Assessment methods

Project work for learning from data in groups of 2-3 persons

Teaching tools

• Digital laboratory
• Google Colab, Python language, PyCaret library

Office hours

See the website of Claudio Sartori