Bayesian Statistics for Machine Learning

3 credits

The courses is for professionals and part of the programme MAISTR ( where participants can study the entire programme or individual courses. The course is part of the course track machine learning and is held online in English.

The course is broken down into:

  • Basic Bayesian concepts
  • Selecting priors, deriving some equations
  • Bayesian inference, Parametric model estimation
  • Sampling based methods
  • Sequential inference (Kalman filters, particle filters)
  • Approximate inference, variational inference
  • Model selection (missing data)
  • Bayesian deep neural networks

Autumn 2024 (Distance (Internet), Varied, 17%)


Advanced level

Application code:


Entry requirements:

Degree of Bachelor of Science with a major in Computer Science and Engineering or Degree of Bachelor of Science in Engineering, Computer Science and Engineering. Including 5 credits statistics and 5 credits machine learning. The degree must be equivalent to a Swedish kandidatexamen or Swedish högskoleingenjörsexamen and must have been awarded from an internationally recognised university. English 6. Exemption of the requirement in Swedish is granted.

Selection rules:

Credits: 100%

Start week:

week: 36

Number of gatherings:


Instructional time:

Various times

Language of instruction:

Teaching is in English.

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