UNLEASH THE POWER OF CAUSAL FORESTS – ENROLL NOW

Enroll in our workshop to kickstart your journey in Causal Machine Learning and Decision Making. The course welcomes practitioners, policy makers, and researchers from both industry and academia.
 

Preview our Forthcoming Workshops.

We offer a two-day workshop on Causal Analysis and Decision Making based on Causal Forests and Decision Trees.

Day 1 covers the fundamentals of Causality, Causal Forests, and Decision Making. We underpin the theory with examples to immediately recognise the practical significance of the theoretical concepts.

Day 2 focuses on applying causal forests and decision trees to conduct heterogeneous effects analyses and optimal treatment assignments. In this hands-on session, we use our Python package mcf (Modified Causal Forest) for estimating treatment effects and creating optimal treatment assignment rules. For questions about the practical implementation of the software that arise after the workshop, we offer a free, two-hour Q&A session one week later, if needed.

The Syllabus gives more information on all topics.

• The theoretical and hands-on sessions enable you to address practical questions about causal relationships and optimal decision-making.
• You can apply state-of-the-art machine learning methods to experimental or observational data.
• You will gain the skills to use these methods in various treatment settings across fields such as economics, medicine, and business.

Experience the benefits of small group learning in our workshops. We limit the number of registrations to just 20 per workshop, ensuring a personalised service and a supportive learning environment. This set-up promotes frequent interactions, meaningful discussions, and individualised feedback, maximising your learning potential. Our teaching and development Team provides support not only during the classes but also assists with questions related to using our software in specific use-cases.