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A Beginner’s Guide to Macroeconomics with AI
Rating: 4.4 out of 5(6 ratings)
354 students

A Beginner’s Guide to Macroeconomics with AI

Build AI-powered economic forecasts with Python while learning GDP, inflation, and unemployment basics.
Created byThe Wealthy Loom Project
Last updated 10/2025
English
English [Auto],

What you'll learn

  • Understand key macroeconomic indicators such as GDP, inflation, and unemployment, and explain their roles in assessing national economic performance.
  • Collect, clean, and visualize real-world economic data using Python libraries and APIs like the Federal Reserve Economic Data (FRED) to uncover economic trends.
  • Apply machine learning models to forecast macroeconomic variables, including time series and regression techniques for practical, data-driven analysis.
  • Build an AI-powered economic forecasting project, developing a functional predictive pipeline that strengthens your portfolio in economics and data science.

Course content

3 sections • 13 lectures • 53m total length

  • Introduction1:50

    Explore macroeconomics fundamentals with AI tools to understand growth, inflation, unemployment, and trade, forecast using machine learning, interpret indicators, and build an AI-assisted real-time macroeconomic dashboard.

  • What is Macroeconomics?2:18

    Macroeconomics studies the economy at large using GDP, inflation, and unemployment to examine performance, policy impact, and top-down data modeling with Python.

  • Key Macroeconomic Indicators3:47

    Identify key macroeconomic indicators like GDP, inflation, and unemployment to assess growth and labor health, and connect stock trends, trade balances, and policy actions to cycles and ai assisted modeling.

  • Understanding GDP3:20

    Explore how gross domestic product measures a country's total output through consumption, investment, government spending, and net exports. Differentiate nominal and real GDP, grasp GDP deflator, and recognize GDP's limitations.

  • Inflation4:32

    Explore how inflation, a key macroeconomic indicator, arises from demand outpacing supply or rising costs, and distinguish demand-pull, cost-push, and built-in inflation with CPI and PPI.

  • Unemployment3:10

    Explore the types of unemployment, frictional, structural, and cyclical, and their links to the natural rate and Okun's law. Learn how trends influence policy decisions and labor market health.

Requirements

  • No prior economics or programming experience is required. This course is designed to be beginner-friendly, though basic familiarity with Python is recommended.

Description

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.

Who this course is for:

  • Students curious about economics, data science, and machine learning.

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