Causal Inference

Columbia University, founded in 1754 and located in New York City, is a world-renowned Ivy League research university that blends rigorous scholarship with an urban, globally-connected campus life. With a wide range of undergraduate and graduate programs across the arts, sciences, engineering, business, and professional fields, Columbia emphasizes intellectual inquiry, interdisciplinary collaboration, and access to the rich cultural and professional resources of New York.

Columbia’s academic strengths are complemented by extensive research facilities, libraries, and centers that support student-led projects and faculty scholarship. The university’s location enables exceptional internship, networking, and cultural opportunities across finance, media, technology, public policy, and the arts. Small seminars, mentorship from leading scholars, and a strong career services network help students translate academic achievement into professional success.

For international students, Columbia offers language support, international student advising, and a diverse campus community drawn from around the world. The university’s commitment to global engagement, combined with its urban setting, makes it an attractive choice for students seeking a rigorous education, significant research opportunities, and direct access to one of the world’s most vibrant cities.

The Causal Inference program is a non-degree course at Columbia University that teaches students how to make inferences about causation. It's a rigorous mathematical survey that helps students understand causal relationships in science, medicine, policy, and business. The course is taught in English and lasts several weeks.

The curriculum covers methods for collecting data to estimate causal relationships, such as matching, sub-classification, and machine learning. Students will learn how to distinguish between causal and non-causal relationships and evaluate different methods for estimating effects. They will also develop skills in statistical analysis and critical thinking.

After completing this program, students can pursue careers as data analysts, statistical consultants, research scientists, policy evaluators, or business intelligence specialists. They can work in industries such as healthcare, finance, or government, where understanding causal relationships is crucial for making informed decisions.