Probabilistic Modeling
A.Y. 2022/2023
Learning objectives
The course of probabilistic modelling aims at enriching the student's choice of methodological tools for data analysis with advanced topics that are not covered by other courses, namely graphical models. In particular, in the graphical modelling module, students will gain knowledge of techniques that provide an elegant framework to compactly represent complex real-wold phenomena, also when the number of variables involved is high.
Expected learning outcomes
Students of this course will acquire a thorough understanding of the theory behind graphical models and the ability to apply these tools to real datasets, through the introduction to specific packages of the R software. In particular, they are required to perform an empirical analysis, using one method from the ones discussed in the class at their choice, proving their comprehension of the topics and their ability to apply them and to discuss and report the results.
Lesson period: Second trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
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
Course currently not available
Lesson period
Second trimester
SECS-S/01 - STATISTICS - University credits: 6
Lessons: 40 hours
Educational website(s)