Based on data from life sciences and medicine, the Workshop introduces predictive mechanistic modelling using Python. We start with the concepts of quantitative changes over time and expand it to include changes in time and space. Our focus will be the understanding and prediction of unexpected, dramatic and catastrophic changes, like a new qualitative shape during differentiation, a fever after infection, having a seizure or migraine attack. We will look at mathematical formalism to describe biochemical reactions and transport; endocrine feedback loops; dynamic switching between physiological states and the origin of temporal oscillations. We will work with simple pre-written functions which we will study, modify, and simulate to create testable predictions.