Spring 2027

Foundations of Artificial Intelligence in Business

An introduction to foundational AI concepts and their applications in business, covering how AI works, its impact on society, and ethical considerations.

offering recorded2 credits
Recorded instructors · Spring 2027 Katie Gaertner

Summary

1 / 3

Recent recorded grades — Spring 2026: 3.78 GPA, 93.3% A/AB (n=30 letter grades).

What you’ll be able to do

  • Explain the basic principles of AI and machine learning.

  • Describe how AI systems learn, process data, and make decisions.

  • Discuss the use of AI in various business fields, and the resulting disruptions.

  • Articulate ethical considerations and challenges surrounding AI.

  • Apply AI tools in personal and professional settings to solve problems, meet user needs, and identify opportunities in business.

Source: UW Guide

Grade history

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average GPA
letter grades
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All recorded terms · compare terms & instructors

Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
GENBUS 707

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Graduate/professional standing

Professors

Spring 2027

Recent recorded grades — Spring 2026: 3.78 GPA, 93.3% A/AB (n=30 letter grades).

Historical instructors & teaching patterns

KATIE GAERTNER is recorded teaching in Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 020Classroom Instruction0 / 500

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
Download part 1

Student experience

the class

Recent recorded grades — Spring 2026: 3.78 GPA, 93.3% A/AB (n=30 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Basic principles of AI and machine learning
  • Use of AI in business fields and resulting disruptions
  • Ethical considerations and challenges of AI

Skills

  • Applying AI tools to solve problems and identify business opportunities
  • Articulating ethical considerations and challenges of AI
  • Describing how AI systems learn, process data, and make decisions

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F
More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1280 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Download part 1
Selected offering source records
GENBUS 707 · Spring 2027

Foundations of Artificial Intelligence in Business

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:231:027213",
    "course_id": "GENBUS 707",
    "course_uid": "course_2e7b306eeb0cb6785494685f",
    "term_id": "1274",
    "source_course_id": "027213",
    "source_subject_id": "231",
    "title": "Foundations of Artificial Intelligence in Business",
    "credits_min": 2,
    "credits_max": 2,
    "typically_offered": "Not Applicable"
  }
]
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Student reviews

Original comments behind the course and instructor summaries.

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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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
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "03f9b032a54c6a7e4203b731c179f8e5466a3fcf77eb00e2c52d89253a8730af",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}