Bayesian data analysis

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 organized on Mondays at 14:15-16:00 (recording is available after the lecture).
• 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.