CS-E407520 - Special Course in Machine Learning and Data Science: Bayesian Workflows, Lectures, 22.4.2024-3.6.2024

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

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
Prerequisites

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.

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Aalto University Code of Academic Integrity and Handling Violations Thereof