Fall 2026

Machine Learning and Artificial Intelligence Models for Business Analytics

Introduces machine learning and AI models for business analytics, covering supervised and unsupervised techniques.

offering recorded2 credits
Recorded instructors · Fall 2026 Zhongtian Chen

Summary

1 / 3

Recent recorded grades — Fall 2025: 3.71 GPA, 87.3% A/AB (n=63 letter grades); Spring 2026: 3.96 GPA, 97.5% A/AB (n=80 letter grades).

Grade history

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

Prerequisites

Course map

ACT SCI 640 or (GEN BUS 656 or concurrent enrollment)

GENBUS 657 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Fall 2026

Recent recorded grades — Fall 2025: 3.71 GPA, 87.3% A/AB (n=63 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

ZHONGTIAN CHEN is recorded teaching in Fall 2025. 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

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 010Classroom Instruction28 / 350
LEC 011Classroom Instruction20 / 350

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

Meeting source records
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Student experience

the class

Recent recorded grades — Fall 2025: 3.71 GPA, 87.3% A/AB (n=63 letter grades); Spring 2026: 3.96 GPA, 97.5% A/AB (n=80 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Additive models, CARTs, bagging/boosting, deep learning, and AI models
  • Unsupervised learning, clustering, and anomaly detection

Skills

  • Developing algorithmic prediction models for supervised learning
  • Applying additive models, CARTs, bagging/boosting, and deep learning
  • Applying unsupervised learning techniques like clustering and anomaly detection

Grades

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

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

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AB
B
BC
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F

Grades over time

Through Spring 2026

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

1283 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 657 · Fall 2026

Machine Learning and Artificial Intelligence Models for Business Analytics

Recorded 2026-09-07
Raw records 
[
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:231:026426",
    "course_id": "GENBUS 657",
    "course_uid": "course_d867856b67bb1895c4ab83ea",
    "term_id": "1272",
    "source_course_id": "026426",
    "source_subject_id": "231",
    "title": "Machine Learning and Artificial Intelligence Models for Business Analytics",
    "credits_min": 2,
    "credits_max": 2,
    "typically_offered": "Not Applicable"
  }
]
Rate My Professors

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 2026-09-07

View the dataset on Hugging Face
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "91063df3832c2054a8fd791544ef29cf9952a8746522f2ddd2e140dcd7c21030",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}