This short course and the individual modules within, aim to introduce the state-of-the-art concepts and tools of Systems Thinking (ST), System Dynamics (SD) and Bayesian Networks (BN) and their applications to complex decision making and problem-solving across a range of fields. The course modules will provide modelling strategies and present some applications from the field of complex system modelling.
The program is made up of 5 modules. Systems Thinking (Module 1), System Dynamics (Beginners and Intermediate levels) and Bayesian Network (Beginners and Intermediate levels). The 5 modules will run over 1 day each, broken into 2 x three hours sessions per module. You can enrol in the full course, comprising of all 5 modules, or enrol in the modules individually to suit your learning requirements.
Dr Oguz 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.
- Introduction to Systems Thinking: Causal Loop Modelling and System Archetypes
- System Dynamics Tool – introduction to SD software VensimPLE
- SD modelling procedure: Dynamics of Stocks and Flows
- SD Model building exercise (Group/individual): Explore several strategies (Scenario Analysis)
- Introduction to Bayes’ theorem; Bayesian inference & Bayesian Networks
- Bayesian Networks in action: Case study examples
- Bayesian Network conceptualisation: Modelling steps and procedure
- Modelling exercise: building a Bayesian Network (group/individual)
Take it step by step
Learn at your own pace, this course is available as individual modules.
|Systems Thinking||$855 – $950||Enrol|
|System Dynamics (Beginner)||$855 – $950||Enrol|
|System Dynamics (Intermediate)||$855 – $950||Enrol|
|Bayesian Networks (Beginner)||$855 – $950||Enrol|
|Bayesian Networks (Intermediate)||$855 – $950||Enrol|
The course aims to introduce the state-of-the-art concepts and tools of Systems Thinking, System Dynamics and Bayesian Networks and their applications to complex decision making and problem-solving across a range of fields.
The methodological focus of these subjects ensures that participants from all disciplines will benefit from this course. Participants will gain key skills for analysing complex problems by understanding the behaviour of system and inherent uncertainties and learn how to build a model in a time-efficient and simple way. The course emphasizes both theory and practice.
After successfully completing this course students should be able to have:
- A fundamental understanding of systems thinking/system dynamics concepts and principles
- A fundamental understanding of Bayes theory and Bayesian Networks concepts and principles
- Describe the components of a complex system
- Build a simple model of a real-world system
- Run model simulations
Who should attend
This course is designed to accommodate a diverse audience, including:
- Decision makers such as government agencies and industry managers/practitioners identifying 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.
To complete the Beginners module, Participants need to have experience building small models and have theoretical knowledge of Systems approach (BN and/or SD).
A laptop computer and freely available BN (GeNIe) and SD modelling (VensimPLE) packages are required. Basic Mathematical and Computer skills are also required.