This workshop covers causal discovery and causal inference, explaining why predictive models and correlations are often insufficient for answering “what if” and intervention-based questions. To address this gap and avoid the usual pitfalls, we introduce the foundations of causal reasoning before applying them to real-world problems. Finally, hands-on sessions enable participants to quickly get started with causal machine learning using Python.