Quantitative Economics: Data Analysis with Python

Traditional economics can feel abstract, but quantitative methods allow you to test theories against real-world data. Start building the practical skills needed to analyze economic phenomena using code. This course transforms your theoretical understanding of economics into practical, quantifiable skills. You will move beyond high-level definitions to actively model foundational concepts, interpret real-world datasets, and derive meaningful conclusions about production, consumption, and distribution using the power of Python. What you'll learn: * Understand core microeconomic concepts like utility maximization and production functions. * Apply Python and modern data structures (like Pandas DataFrames) to organize and clean economic datasets. * Practice modeling complex scenarios, such as income inequality and wealth distribution analysis. * Analyze the results of Randomized Controlled Trials (RCTs) using basic statistical inference methods. * Configure basic data visualizations to communicate complex economic findings effectively. * Master the process of deriving cost functions and analyzing market equilibrium. We begin by establishing fundamental economic definitions and setting up your Python environment. We then progress through core microeconomic theory, applying data handling and statistical techniques to model concepts like cost functions and experimental results before concluding with advanced topics in distribution analysis. This course is designed for absolute beginners in quantitative economics and Python programming. No prior experience with data science, statistics, or coding is required. Begin your journey into quantitative economic analysis today.