In this week, you will get a comprehensive understanding of robustness, resilience and sustainability. You will learn the self-organized criticality in the complexity system and self-similarity including the fractals, power law, universality and phase transition diagram. This week includes a case study of the subak system in Bali, which will help you further understand the tragedy of the commons. Lastly, you will get introduced to the resilience of a swarm.

In this week, you will get a basic understanding of tipping point and regime shifts, and their applications in forecasting. You will understand the phase transition diagram, criticality and landau theory. Additionally, you will review examples on early warnings and forecasting in earthquakes and stock markets.

In this week, you will learn about Agent-Based Modeling: what it is, how it works, why it is used and how to use it. Then, you will try a Jupyter Notebook exercise on Schelling’s Segregation Model. You will also learn how to build an ABM using qualitative data from observations and interviews and then validate and calibrate an ABM through examples. In the end, you'll review how to use ABM for policy assessment.

In this week, you will get a comprehensive understanding of what a complex network is and how to measure on networks in terms of nodes and paths. You will get introduced to different types of random network and small-world networks that will help you have a better understanding. You will also discuss the robustness of a network, percolation transitions and real-world examples.Lastly, you will review complex networks and their attributes before looking at different network models.