Checking date: 19/05/2023

Course: 2023/2024

Reasoning under Uncertainty
Master in Applied Artificial Intelligence (Plan: 475 - Estudio: 378)

Coordinating teacher: CABRAS , STEFANO

Department assigned to the subject: Statistics Department

Type: Electives
ECTS Credits: 3.0 ECTS


The main objective of this course is to use concepts related to Bayesian inference for solving problems in AI. These concepts and posterior approximation techniques are illustrated by presenting some relevant Bayesian models for AI. These models will be related to regression and Causal Inference.
Skills and learning outcomes
Assessment System
  • % end-of-term-examination 40
  • % of continuous assessment (assigments, laboratory, practicals...) 60

Calendar of Continuous assessment

The course syllabus may change due academic events or other reasons.

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