Operations Analysis

Operations Analysis contains five modules structured to build participant knowledge and skills as they progress through the course.

Module 1. Introduction to Systems Thinking: In this module, students will learn about framing an operational problem using systems thinking principles. Topics in this module include problem framing, systems dynamics, gap analysis, and systems optimisation.

Module 2. Foundational Computational Programming: In this module, students will learn about writing and debugging scripts for data processing. Topics in this module include an introduction to several programming languages and computational tools such as MATLAB/GNU Octave, Excel, VBA and SQL. The module also discusses the principles of scripting and building relational databases.

Module 3. Data Analysis and Visualization: In this module, students will learn about creating data visualisations to support hypothetical decision-making scenarios. Topics in this module include fundamentals of data modelling, data visualisation and quantitative/qualitative data representation methods.

Module 4. Quantitative Analysis Techniques: By completing this module, students will be able to apply statistical methods to analyse system performance data. Topics in this module include an introduction to probability theory and statistics, Bayesian and regression analysis, and Monte Carlo Simulation.

Module 5. Complex and Wicked Problem Solving: By completing this module, students will be able to develop strategic approaches to deal with multifaceted complex problems using techniques such as risk management, and root cause analysis. They will also learn about various types of modelling and simulation techniques to help them with these, such as agent-based, discrete event, and spatial modelling.