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Uppsala University
Advanced Probabilistic Machine Learning
This is an advanced course in machine learning, focusing on modern probabilistic/Bayesian methods, including Bayesian linear regression, generative models, and graphical models. Additionally, it covers methods for exact and approximate inference in these models, such as Monte Carlo methods, variational inference, an…
- Higher education
- Information unavailable
- 31 August 2026
- Uppsala
- Information unavailable
- 33 %
Overview
This is an advanced course in machine learning, focusing on modern probabilistic/Bayesian methods, including Bayesian linear regression, generative models, and graphical models. Additionally, it covers methods for exact and approximate inference in these models, such as Monte Carlo methods, variational inference, and the Laplace approximation. The course encompasses both theory (e.g., derivations and proofs) and practice. The practical part will be implemented using Python.
Admission scores
Entry requirements
120 credits including Probability and Statistics, Linear Algebra II, Single Variable Calculus, Statistical Machine Learning, a course in several variable analysis and a course in introductory programming. Proficiency in English equivalent to the Swedish upper secondary course English 6.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2026-08-31
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.uu.1rt705.11801.20262
- Last checked
- 2026-09-23T10:39:41.205927+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
Programme content
Study structure
Application and important dates
- Programme or course starts
- Programme or course ends
Salary and salary distribution
Common occupations after graduation
Students
Geographical background
Previous upper-secondary schools and programmes
Completion and outcomes
About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.uu.1rt705.11801.20262
- Offering identity in the source
- e.uoh.uu.1rt705.11801.20262
- Education-form source code
- HS
- Education code in the source
- 1RT705
- Change time according to the source
- 2026-03-09T12:14:17
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.