Bayesian Analysis (online)

This module will provide an introduction to Bayesian analysis with an emphasis on concepts in Bayesian theory and practice. A focus throughout will be on statistical programming via the Stan probabilistic programming language.

Accordion / FAQ component

Most modules require a 2.2 degree in a related discipline or equivalent professional experience. Should you have any queries regarding your eligibility, please contact us at

N.B. Required to have completed mathematics and statistics modules that contain elements of linear algebra (specifically matrix manipulation) and calculus.


By the end of this module students should be able to understand and implement Bayesian statistical methods to a wide variety of data sets. They should be able to check the model and give a critique of the Bayesian process as opposed to its Frequentist counterpart.

Indicative content covered in this moduel will include:

  • A recap of the some basic concepts in probability theory.
  • Introduction to Bayesian statistics
  • Bayesian linear regression
  • Hierarchical models
  • Model comparison

Learn from world renowned academic staff in Ireland’s leading, future focused and globally recognised colleges.

Gain an accredited NFQ qualification/micro credential that you may count towards a full award if you so wish in the future.

Previous modules may be used as recognition of prior learning towards Advance Centre degree programmes.

Equip yourself with the latest in demand skillset, tools, know-how and knowledge to succeed in your career.

Gain a competitive edge, influence growth and steer strategic goals in your organisation upon completion of your studies with the Advance Centre.

Yes, if you complete this module it can be credited as part of the MSc Data Analytics or Professional Diploma Data Analytics PT

Detailed Course Information

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