SDSC6003 - Bayesian Data Analysis

Offering Academic Unit
School of Data Science
Credit Units
Course Duration
One Semester
Course Offering Term*:
Semester A 2023/24

* The offering term is subject to change without prior notice
Course Aims

The aim of this course is to provide students with an understanding of Bayesian statistics and to build students’ ability to develop Bayesian models for practical data analysis problems. Students will learn to implement Bayesian models with Markov chain Monte Carlo and other numerical methods in software (Matlab or R) and interpret the results. In addition, they will learn about the Bayesian perspective and its underlying theory.

Assessment (Indicative only, please check the detailed course information)

Continuous Assessment: 55%
Examination: 45%
Examination Duration: 3 hours
Detailed Course Information


Useful Links

School of Data Science