Advanced Topics in Machine Learning
People
Course director
Carman M. J.
Course director
Assistant
Assistant
Assistant
Description
The course aims at entertaining students on advanced topics in machine learning by both touching technologies/methodologies and applications. Particular attention will be devoted to the use of Large Language Models technologies.
Objectives
The goal of the course is to expose students to advanced topics in machine learning so as to complement and enrich material seen in basic machine learning courses.
Sustainable development goals
- Indusrty, innovation and infrastracture
- Sustainable cities and communities
Teaching mode
In presence
Learning methods
The teaching modality blends frontal teaching done by the instructors -we will also invite international fellows to deliver some lectures- and presentations done by groups of students on hot machine learning topics on provided material. Assignments will be given to groups of students to perfect some topics understanding.
Examination information
Assignments and presentations done by the students.
Education
- Master of Science in Artificial Intelligence, Lecture, 2nd year
- Master of Science in Computational Science, Lecture, Elective, 2nd year
- Master of Science in Informatics, Lecture, Artificial Intelligence, Elective, 1st year
- Master of Science in Informatics, Lecture, Artificial Intelligence, Elective, 2nd year
- PhD programme of the Faculty of Informatics, Lecture, Elective, 1st year (4.0 ECTS)
Prerequisite
- Machine Learning, Wand M., Ashley D. R., Faccio F., Gopalakrishnan A., Herrmann V., Kirsch L., SA 2021-2022
- Machine Learning, Alippi C., Adorni G., Butera L., Riva M., SP 2022
