Workshop: Software Tools for Machine Learning

A.Y. 2024/2025
3
Max ECTS
36
Overall hours
Language
English
Learning objectives
In this course the students will learn how to process data and solve complex problems with a set of available computational tools. The tools will be presented with a hands-on approach, based on the computational tasks at hand, and with exemplary codes. Additionally the students will understand how to manage different types of data (e.g. categorical versus numerical) and what type of algorithm to use. Particular attention will also be devoted to the use of a High Performing Computational facility to efficiently solve the most demanding computational tasks.
Expected learning outcomes
At the end of the course, students are expected to have the following skills:

1) formulate a given problem in a mathematical or algorithmic way
2) understand how to preprocess the data
3) distinguish classification from regression and Clustering computational tasks
4) program a data analysis pipeline
5) efficiently solve a problem on a HPC facility
Single course

This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.

Course syllabus and organization

Single session

Lesson period
Second semester
- University credits: 3
Humanities workshops: 36 hours