Syllabus(课程计划)

DS & AI for Economists,Fall 2025

Course Description

This course serves two primary objectives for students already versed in core data analysis methods.

First, it equips students with practical experience in harnessing AI technologies to enhance analytical productivity while fostering critical discussions on human agency in data analysis. As AI capabilities expand, the course examines the evolving roles of artificial intelligence and human expertise across analytical domains.

Second, the course focuses on leveraging large language models and programming tools to acquire, process, and analyze unstructured big data, including spatial data analysis, web scraping, text analysis, and OCR applications. Rather than emphasizing theoretical foundations, the course adopts a hands-on approach through real-world case studies and project-based learning.

The course addresses a fundamental question: how can economists effectively integrate AI into their research toolkit while maintaining analytical rigor? Through guided exploration of AI-assisted workflows, students develop both technical competencies and critical perspectives on artificial intelligence in economic research.

Students will complete empirical research projects demonstrating the integration of AI tools with traditional economic analysis methods.

Evaluation

  • Participation（\(10\%\)）

  • Proposal Presentations for Group Projects (\(50\%\))

  • Preliminary results for Group Projects (\(40\%\))

Textbooks

The course have no required textbooks, but the following books and online resources are recommended for further reading and reference: