LEARNING OUTCOMES
After the course, the student can explain the central concepts in Bayesian statistics, and name steps of the Bayesian modeling process. The student can recognize usages for common (i.e. those presented during the course) statistical models, and formulate the models in these situations. The student can compare the most popular Bayesian simulation methods, and implement them. The student can use analytic and simulation based methods for learning the parameters of a given model. The student can estimate the fit of a model to data and compare models.
Credits: 5
Schedule: 02.09.2024 - 05.12.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Aki Vehtari
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
Bayesian probability theory and bayesian inference. Bayesian models and their analysis. Computational methods, Markov-Chain Monte Carlo.
Assessment Methods and Criteria
valid for whole curriculum period:
Assignments (67%) and a final project work with presentation (33%). Minimum of 50% of points must be obtained from both the assignments and the project work.
Workload
valid for whole curriculum period:
Lectures 10x2h, computer exercises 10x2h, independent studying (text book, programming, home assignment and project reports), project presentation
DETAILS
Study Material
valid for whole curriculum period:
Book "Bayesian Data Analysis, 3rd ed", lectures, videos, chapter notes, demos, assignment instructions, website https://avehtari.github.io/BDA_course_Aalto/
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
1 No Poverty
2 Zero Hunger
3 Good Health and Well-being
4 Quality Education
5 Gender Equality
6 Clean Water and Sanitation
7 Affordable and Clean Energy
8 Decent Work and Economic Growth
9 Industry, Innovation and Infrastructure
10 Reduced Inequality
11 Sustainable Cities and Communities
12 Responsible Production and Consumption
13 Climate Action
14 Life Below Water
15 Life on Land
16 Peace and Justice Strong Institutions
17 Partnerships for the Goals
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn I - II
2025-2026 Autumn I - II