The world we live in is characterized by an exponential increase in data that accurately describe our daily lives, referred to as "big data." To harness this information, new methods like Machine Learning and Artificial Intelligence have emerged, enabling high-dimensional statistical analyses. The aim of this course is to provide students with an introduction to modern data-driven learning, particularly for causal economic analysis. While we will cover the theoretical foundations, our emphasis will be on application and learning how and when to use these methods effectively, as well as identifying their limitations.The coursework comprises homework assignments utilizing simulated and real-world data, weekly online discussions on real-life data analysis problems, and a group project in the form of a case study. We will use R as our primary data analysis software and devote a significant amount of class time to teaching how to efficiently code various analytical models. Prior coding experience is welcome but not necessary, as everything you need to know about R will be taught from scratch.
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