Spring 2027

Data Visualization & Cloud Technologies

Data Visualization & Cloud Technologies provides experience in data visualization and cloud technologies to support business analytics, including building scalable data warehouses and deploying machine learning models.

offering recorded2 credits
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 3

Recent recorded grades — Spring 2025: 3.90 GPA, 97.6% A/AB (n=41 letter grades); Fall 2025: 3.85 GPA, 90.0% A/AB (n=40 letter grades); Spring 2026: 3.87 GPA, 91.3% A/AB (n=23 letter grades).

What you’ll be able to do

  • Create compelling data visualizations and dashboards.

  • Explain the cloud landscape for business analytics - i.e. vendors, services, and costs.

  • Setup and manage a cloud data warehouse.

  • Build and deploy a machine learning model in the cloud.

  • Analyze big data in a cloud environment.

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

Graduate/professional standing or declared in graduate Business Exchange program. Not open to students with credit forGEN BUS 720 or 780.

      • Graduate/professional standing
      • declared in graduate Business Exchange program
      take one
    • not eligible with
    take all
GENBUS 883 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
  • All of
    • Any of
      • Graduate/professional standing
      • declared in graduate Business Exchange program
    • Not eligible with

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

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

Calendar & sections

Spring 2027

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SectionModeEnrolled / capacityWaitlist

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

Meeting source records

No records available.

Student experience

the class

Recent recorded grades — Spring 2025: 3.90 GPA, 97.6% A/AB (n=41 letter grades); Fall 2025: 3.85 GPA, 90.0% A/AB (n=40 letter grades); Spring 2026: 3.87 GPA, 91.3% A/AB (n=23 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Data visualization
  • Cloud technologies
  • Scalable data warehouses
  • Big data analysis
  • Machine learning model development and deployment

Skills

  • Creating compelling data visualizations and dashboards
  • Explaining the cloud landscape for business analytics including vendors, services, and costs
  • Setting up and managing a cloud data warehouse
  • Building and deploying machine learning models in the cloud
  • Analyzing big data in a cloud environment

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

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

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.

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Selected offering source records
GENBUS 883 · Spring 2027

Data Visualization & Cloud Technologies

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": "1274:231:026422",
    "course_id": "GENBUS 883",
    "course_uid": "course_04e99793b32064d1d2d6fa22",
    "term_id": "1274",
    "source_course_id": "026422",
    "source_subject_id": "231",
    "title": "Data Visualization & Cloud Technologies",
    "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": "f5f04206d289ae6dc3c9359651bda1208f183a0c8a2d338fe487b848a0a7e33c",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}