Causal Inference

Causality Models, Reasoning and Inference: Causal Data Science Course

DSA ADS Course - 2021

Causal Analysis, Causality Models, Causal Inference

Discuss causal analysis and how it applies to many different fields like health policy and medical practice, public policy, business decisions, statistics, artificial intelligence, economics, philosophy, cognitive science, and others. Review probabilistic, manipulative, counterfactual, and structural approaches to causation and apply simple mathematical tools for studying the relationships between causal connections and statistical associations.

Introduction to Graphical Models and Bayesian Networks

DSA ADS Course - 2022

Graphical Models, Bayesian Networks, Applied Probability, Probabilistic Causation, Causal Inference

Applied data scientists require high-level understanding of probability theory and specialized techniques to design systems and solve problems in the real world.  Graphical model formalism provides a natural framework for the design of new data science systems.

Pages