Spring 2027

Data Exploration with SQL and Artificial Intelligence (ai)

Data Exploration with SQL and AI teaches students to analyze data using SQL and integrate AI to generate and audit SQL code for accuracy.

offering recorded2 credits
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 3

Recent recorded grades — Spring 2025: 3.92 GPA, 100.0% A/AB (n=40 letter grades); Fall 2025: 3.86 GPA, 92.9% A/AB (n=42 letter grades); Spring 2026: 3.90 GPA, 95.2% A/AB (n=21 letter grades).

What you’ll be able to do

  • Construct a variety of SQL statements.

  • Query and prepare data in response to business questions.

  • Utilize AI to explore data, generate SQL, and audit the outputs.

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

    • Graduate/professional standing
    • declared in graduate Business Exchange program
    take one
GENBUS 882 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
  • Any of
    • Graduate/professional standing
    • declared in graduate Business Exchange program

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

Schedule loads here as you scroll.

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: 3.92 GPA, 100.0% A/AB (n=40 letter grades); Fall 2025: 3.86 GPA, 92.9% A/AB (n=42 letter grades); Spring 2026: 3.90 GPA, 95.2% A/AB (n=21 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • SQL data exploration and analysis
  • AI integration for SQL generation
  • Auditing and troubleshooting AI outputs

Skills

  • Writing SQL statements
  • Querying and preparing data for business questions
  • Using AI to generate and audit SQL

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.

Download part 1
Selected offering source records
GENBUS 882 · Spring 2027

Data Exploration with SQL and Artificial Intelligence (AI)

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": "1274:231:026421",
    "course_id": "GENBUS 882",
    "course_uid": "course_8a0780473a26d22f1a8670c2",
    "term_id": "1274",
    "source_course_id": "026421",
    "source_subject_id": "231",
    "title": "Data Exploration with SQL and Artificial Intelligence (AI)",
    "credits_min": 2,
    "credits_max": 2,
    "typically_offered": "Not Applicable"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews

No records available.

Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
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": "5eb3e83727dbef3581e0867bada40e19f1d813dbfe6c604dd2eb22553f8724bc",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}