Fall 2026

Machine Learning in Applied Economic Analysis

Teaches machine learning methods and applications for analyzing economic issues with large datasets.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Fall 2023: 3.60 GPA, 75.0% A/AB (n=20 letter grades); Fall 2024: 3.86 GPA, 90.9% A/AB (n=11 letter grades); Fall 2025: 3.92 GPA, 94.7% A/AB (n=19 letter grades).

Grade history

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average GPA
letter grades
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Prerequisites

Course map

A A E 636 or ECON 704

AAE 722

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Professors

Fall 2026

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Calendar & sections

Fall 2026

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Student experience

the class

Recent recorded grades — Fall 2023: 3.60 GPA, 75.0% A/AB (n=20 letter grades); Fall 2024: 3.86 GPA, 90.9% A/AB (n=11 letter grades); Fall 2025: 3.92 GPA, 94.7% A/AB (n=19 letter grades).

difficulty & workload

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Topics

  • Data mining, regression, neural networks, random forests, causal inference, unsupervised learning

Skills

  • Machine learning techniques for economic data
  • Applying ML to economic issues

Grades

Latest available · Fall 2025— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
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F

Grades over time

Through Fall 2025

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Sources & history

UW–Madison

Catalog & offerings

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Dataset & model

Recorded 2026-09-07

View the dataset on Hugging Face
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
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": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "7856a65d04241a018cc26266f284664130a0d2c3bcca9536477f3e9e0654d872",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}