Spring 2027

Advances in Artificial Intelligence for Economists

Introduction to basic AI concepts and their use in economics, covering general principles, specific economic applications, and implementation using economic data.

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Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 2

Lectures are small, with a median of 10 enrolled students in the recorded sections.

Section enrollment · Fall 2026 snapshot ↗

What you’ll be able to do

  • Explain basic Artificial Intelligence methods and how they are commonly applied to economic data

  • Classify differences and similarities between econometrics and AI methods

  • Evaluate advantages and disadvantages of different econometrics and AI methods

  • Apply AI tools and methods to economic data

Source: UW Guide

Grade history

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average GPA
letter grades

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Prerequisites

Course map

ECON 725

ECON 771

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Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

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Calendar & sections

Spring 2027

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Student experience

the class

Introduction to the basic concepts of artificial intelligence and its use in economics. Covers general principles and specific economic applications. Discusses implementing these approaches using economic data.

difficulty & workload

No workload feedback recorded.

Topics

  • Basic concepts of artificial intelligence
  • Specific economic applications of AI
  • Implementing AI approaches using economic data
  • Comparison of econometrics and AI methods

Skills

  • Explain basic AI methods and their application to economic data
  • Classify differences and similarities between econometrics and AI methods
  • Evaluate advantages and disadvantages of econometrics and AI methods
  • Apply AI tools and methods to economic data

Grades

Instructor

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Sources & history

UW–Madison

Catalog & offerings

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Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "14fe365c741791c2ab6640ce856febda7c9ec3a31769227da5b3e84deca7a52c",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}