Causal AI Book and Workshop

This body contains materials related to the book Causal AI as well as the workshop and graduate school course based on the book. The book, workshop, and course focus on intervention-based reasoning, causal inference algorithms, counterfactuals, and the integration of causal structure into modern ML systems.

Contents

• book directory – Jupyter notebooks containing code from the book.
• workshop.md – Description of the Causal Modeling in Machine Learning workshop, including schedule, learning objectives, and software tools.
• syllabus_NEU.md – A graduate course syllabus from Northeastern University covering causal modeling, do-calculus, counterfactual reasoning, and causal ML applications.
• tutorials directory – A directory of code tutorials used in the workshop and graduate course.
• projects directory – A directory of past student projects from the graduate course.

Usage

Use this repository to:

• Load and run code from the book.
• Prepare or adapt the workshop for conferences, symposia, or internal trainings.
• Reference the graduate syllabus for a semester-long academic course on causal modeling.
• Build or extend materials on causal inference, causal ML, and counterfactual modeling in your own teaching or research practice.

All materials in this repository are open and reusable for educational and research purposes.