LEARNING OUTCOMES
In this seminar, we
dive into some of the essential steps of Bayesian modelling workflows. You will
become familiar with available software tools that can support different
aspects of modelling like prior sensitivity checks, choosing regularising
priors or using model comparison and model averaging techniques. You will gain
hands-on experience working with your own modelling problem.
Credits: 5
Schedule: 22.04.2024 - 03.06.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Aki Vehtari
Contact information for the course (applies in this implementation):
We will make minimal use of MyCourses in this seminar. You can find all information and updates about schedule, content, assessment, and syllabus on the course webpage.
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Student selection: students should have (1) successfully completed the course CS-E5710 Bayesian Data Analysis and (2) should be Master students or doctoral researchers.