The objective of this lab is to show an example of the use of artificial intelligence in the field of software engineering. We will use supervised learning as well as natural language processing techniques to create a classifier aimed at categorizing tickets describing bugs. For this, we will use a ticket data set from the scientific publication by Herzig et al.This dataset contains 5591 tickets from 3 large open-source projects: HTTPClient 1, Jackrabbit 2 and Lucene 3. These tickets have been manually annotated and therefore have “reliable” labels, which helps to avoid bias or classification errors.