A modern introduction that combines cloud-based computational notebooks, learning apps, and AI tools.
Zero Installation • Learning Apps • AI Support
Learning econometrics should be a more accessible and interactive experience.
Review statistical principles and econometric examples from Cameron's (2022) textbook.
Run Python code directly in the cloud using Google Colab and its powerful AI features. Regressions use the new pyfixest package for estimation, inference, and reporting.
Explore key concepts with interactive web apps — sliders, toggles, and real-time charts for every chapter. No coding required.
Leverage Google's NotebookLM and other AI tools for interactive study, code explanations, and deep dives into complex concepts.
Listen to the metricsAI podcast to learn more.
Let's review econometrics concepts through friendly podcast conversations.
Google Colab notebooks provide an interactive programming environment where AI tools generate code, explain errors, and provide conversational guidance to accelerate learning.
Video source: Julianne DeMars-Smith and Key Jung Lee from Google Research
Click the badge to launch any chapter instantly in your browser. Below the badge, find additional resources for each chapter including slides, quizzes, and a podcast overview.
The learning materials of metricsAI are based on the contents of these books.
An Introduction Using Cloud-based Python Notebooks
by Carlos Mendez
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Computational Python Notebooks and AI learning tools
Associate Professor, Nagoya University, JAPAN.
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Original Textbook, Stata/R/Gretl Code, Datasets, PDF Slides
Professor Emeritus, University of California, Davis, USA.
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