Overview
After describing the fundamentals of Bayesian inference, this course will examine several detailed aspects including: the specification of prior and posterior distributions, Bayesian decision theoretic concepts, the ideas behind Bayesian hypothesis tests, model choice and model averaging, and various model types such as hierarchical and mixture models. An important part … For more content click the Read More button below.
Material is delivered 100% online through a series of self-guided lessons which include challenges, practice questions and videos. Questions can be asked on the discussion forum. Webinars will be held to guide students through the material and to help answer further questions that cannot be raised in the discussion forum.
Conditions for Enrolment
Must be enrolled in 5646 Graduate Diploma in Data Science or 8646 Master of Data Science.
Delivery
Fully online - Intensive
Fees
Type | Amount |
---|---|
Commonwealth Supported Students (if applicable) | $556 |
Domestic Students | $4800 |
International Students | $4800 |
Pre-2019 Handbook Editions
Access past handbook editions (2018 and prior)