Causal Inference

Dive into a comprehensive lecture on Causal Inference presented by Adèle H. Ribeiro at the Nordic Probabilistic AI School (ProbAI) 2023. Explore the fundamental concepts and advanced techniques in causal inference, a crucial field at the intersection of statistics, machine learning, and artificial intelligence. Learn how to identify causal relationships, estimate causal effects, and make robust predictions in complex systems. Gain insights into the latest methodologies and tools used in causal inference, including graphical models, potential outcomes, and structural causal models. Discover practical applications of causal inference in various domains such as healthcare, economics, and social sciences. Access supplementary materials and code examples through the provided GitHub repository to enhance your understanding and implementation skills. This in-depth lecture, running for 2 hours and 24 minutes, offers a solid foundation for researchers, data scientists, and AI practitioners looking to incorporate causal reasoning into their work and make more informed decisions based on causal relationships.