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Bayesian data analysis

Individual course

Max amount of FITech students: 100

Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course.

Mastering the prerequisite skills is very important in order to complete this course.

Course content:

  • Bayesian probability theory and bayesian inference
  • Bayesian models and their analysis
  • Computational methods, Markov-Chain Monte Carlo

After the course, the student can

  • explain the central concepts in Bayesian statistics, and name steps of the Bayesian modeling process.
  • recognize usages for common (i.e. those presented during the course) statistical models, and formulate the models in these situations.
  • compare the most popular Bayesian simulation methods, and implement them.
  • use analytic and simulation based methods for learning the parameters of a given model.
  • estimate the fit of a model to data and compare models.

Lectures (online) will be organized on Mondays at 14:15-16:00. Exercise sessions (Otaniemi) will be held on Wednesdays, Thursdays and Fridays.

More information on Aalto University’s course page.

You can get a digital badge after completing this course.

Responsible teacher

Aalto University
Aki Vehtari

Further information about the studies

Aalto University
FITech ICT contact person

Contact person for applications

FITech Network University
Monica Sandberg, Student services specialist
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ICT Studies
AI and machine learning
Course code:
0 €
Teaching period:
Application deadline:
Application period has ended
Host university:
Aalto University
Study is open for:
Adult learner,
Degree student
Teaching methods:
Place of contact learning:
General prerequisites:
Differential and integral calculus, basics of probability and statistics, basics of programming (R or Python). Recommended: matrix algebra.
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