Risk Assessment and Decision Analysis: Bayesian Networks in Action

Overview

The program consists of two BN modules: Beginner (Day1) and Intermediate (Day2) levels. Each module runs for one day, comprising four 75-minute sessions, including two 15-minute tea breaks and one 30-minute lunch break. Participants can choose to enrol in the complete course, which covers both modules, or select individual modules to suit their specific learning needs.

In addition, participants will have the opportunity to learn relevant software tools used in BN modelling. This practical aspect of the course will equip participants with essential skills to build and run BN models, enhancing their ability to apply BN to assess risk and make informed decisions.

Through this course, participants will gain comprehensive knowledge, practical skills, and relevant software proficiency in BN, enabling them to approach complex problems and decision-making with confidence.
 

Learning outcomes

After successfully completing this course participants should be able to:

• A fundamental understanding of Bayes theory and Bayesian Networks concepts and principles
  
• Describe the components of a complex system, and Bayes principals
• Build a simple model of a real-world the system using the software package (Learning by doing experience)
• Run model simulations (Learning by doing experience)
   

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 connecting the key ideas learnt from other courses.

Prerequesties:

A laptop computer and freely available BN modelling package are required.

Required Software BN modelling package (GeNIe) is freely available.

Presenters

Dr. Oz Sahin is an expert systems modeller, specializing in managing assets and resources, assessing risks, and adapting to climate change. His research interests include sustainable built environments, climate change adaptation, risk assessment, integrated water-energy-climate modelling, decision support systems, coupled System Dynamics and GIS modelling, Bayesian Network modelling, multiple criteria decision analysis, and operational research methods. With over 160 publications, Dr. Sahin has made significant contributions to systems modelling, showcasing his in-depth knowledge and expertise.