A Beginner’s Guide to Macroeconomics with AI

A Beginner’s Guide to Macroeconomics with AI introduces students to the foundational concepts of macroeconomics—such as GDP, inflation, and unemployment—while showing how artificial intelligence and machine learning can be used to analyze and forecast real-world economic trends. Through a hands-on, project-based approach, learners will pull live economic data from trusted sources like the Federal Reserve Economic Data (FRED) API, clean and preprocess it using Python, and apply machine learning models to predict key macroeconomic indicators.

This course bridges economics, data science, and AI, making complex forecasting concepts accessible to high school and college students interested in economics, programming, or data analysis. Step by step, students will build a functional economic forecasting pipeline and create a simple predictive model that can be customized or extended for future projects. By combining theory and practice, the course equips learners with interdisciplinary skills relevant to careers in data science, finance, research, and AI development. Its project-based structure encourages portfolio development and experiential learning, helping students strengthen both analytical and technical abilities. The course appeals to aspiring economists, data enthusiasts, and AI beginners who want to see concrete applications of machine learning in economics. Promotion opportunities include partnerships with student economics clubs, data science communities, LinkedIn, and STEM education platforms.

By the end, students will have a clear understanding of macroeconomic principles, experience working with real data, and the confidence to explore AI-driven economic forecasting on their own.