Bayesian Statistics for Machine Learning
The courses is for professionals and part of the programme MAISTR (hh.se/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
Education occasions
Application open
Start date:
End date:
Pace of study: One-sixth-time
Teaching form: Distance
Language of instruction: Teaching is conducted in English.
Instructional time: Mixed-time
Selection information: Higher education credits: 100%: More information on selection rules
Application code: HH-13201
Meetings: 0
Level: Second cycle
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 or English level 2. Exemption of the requirement in Swedish is granted for those with foreign grades.
Tuition fee:
For applicants with citizenship outside the EU/EEA and Switzerland: More information about tuition fees
First semester: 7550 SEK
The entire education: 7550 SEK
