Bayesian Networks (Beginner)

Module 4 - from the Techniques and Tools for Solving Complex Problems course. This course is an introduction to Bayesian Networks.

About this event

Area of Interest: Capability

Course overview

Bayesian Networks (Beginner) is the fourth module from the Techniques and Tools for Solving Complex Problems Course. The full program is made up of 5 modules, including: Systems Thinking, System Dynamics (Beginners and Intermediate levels) and Bayesian Networks (Beginners and Intermediate levels).

Learners can choose to enrol in single modules or the entire program. Click here for more information on the full course, or to view other modules.

Bayesian Networks (Beginner)

  • Introduction to Bayes’ theorem and Bayesian inference
  • Bayesian inference: Real world examples
  • Introduction to Bayesian Networks
  • Bayesian Networks in action: Case study examples
  • Bayesian Network conceptualisation: Modelling steps and procedure

This short course will introduce the state-of-the-art concepts and tools of Bayesian Networks, its applications to complex decision making and problem-solving across a range of fields. The course will provide modelling strategies and present applications from the field of complex system modelling.

Pre-requests: A laptop computer and freely available BN and SD modelling packages are required. Basic Mathematical and Computer skills are also required.

Required Software: Freely available BN (GeNIe) and SD modelling (VensimPLE) packages.

Delivery Mode: On-campus and remote - you choose how you would like to attend.

Who should attend?

This course is designed to accommodate a diverse audience, including:

  • Decision makers such as government agencies and industry managers/practitioners to help identify problem intervention and new areas of investment.
  • Researchers and academics who are seeking a new research tool.
  • Students studying across defence, business, public health and engineering might find these courses complement or connect the key ideas learnt from other courses.

Courses Outline

Each module is approx. 6 hours long (two 3-hour sessions) and will be delivered on-campus and/or online. Learners can choose to enrol in single modules or the entire program. Each module will include a range of case studies, guest speakers, scenarios, research and key concept areas.

There are two level of courses are offered - beginner and intermediate:


  • This module is intended for participants that are new to Systems concept and have no or a little experience with Systems modelling.
  • No statistical or specific mathematical education is required. Only basic understanding of computer skills is needed.


  • This module in the sequence of Systems modelling courses is intended for participants who want to go to next step, building models dealing with more advanced concepts.
  • Prerequisites: To complete the Beginners module, or Participants need to have experience building small models and have theoretical knowledge of Systems approach (BN and/orSD).



Dr Sahin

Dr Oguz (Oz) Sahin is a systems modeller with specialised expertise in a range of modelling approaches to problems of asset and resource management, risk assessment and climate change adaptation. His research interests include: sustainable built environment; climate change adaptation risk assessment; ecosystem based approaches; integrated water, energy and climate modelling; integrated decision support systems using coupled system dynamics and GIS modelling; Bayesian Network modelling, multiple criteria decision analysis, operational research methods and models. Dr Sahin authored or co-authored more than 150 refereed publication outputs.