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 contents
- Bayesian probability theory and bayesian inference
- Bayesian models and their analysis
- Computational methods, Markov-Chain Monte Carlo
Learning outcomes
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.
Teaching schedule
It is possible to take the course online except for the final project presentation which is arranged on campus.
- Lectures will be organised on Mondays at 14:15-16:00 (recording is available after the lecture).
- Exercise sessions (Otaniemi) will be held on Wednesdays and Thursdays.
More information on Aalto University’s course page.
You can get a digital badge after completing this course.