Spring 2027

Competing Through Analytics

Introduces business analytics, machine learning, and AI from a managerial perspective, covering data capture, data mining trends, converting insights to action, and organizational readiness.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 2

Recent recorded grades — Fall 2025: 3.60 GPA, 75.0% A/AB (n=20 letter grades).

What you’ll be able to do

  • Describe different types of analytics and their uses in relation to their industries: descriptive, predictive and prescriptive.

  • Articulate the value of different types of structured and unstructured data from varying sources such as social media, CRM systems, IoT sensors, etc.

  • Identify the strategic opportunities for improving efficiency, growth, and innovation using data and analytics.

  • Explain the new-found challenges related to Ethical AI and Algorithmic Bias.

Source: UW Guide

Grade history

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average GPA
letter grades
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Prerequisites

Course map

Graduate/professional standing or declared in graduate Business Exchange program

    • Graduate/professional standing
    • declared in graduate Business Exchange program
    take one
OTM 703

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

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Student experience

the class

Recent recorded grades — Fall 2025: 3.60 GPA, 75.0% A/AB (n=20 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Business analytics, machine learning, and artificial intelligence from a managerial perspective.
  • Data capture opportunities, data mining trends, converting analytics insights into action, and organizational readiness.

Skills

  • Describing analytics types, articulating data value, identifying strategic opportunities, and explaining ethical AI challenges.

Grades

Latest available · Fall 2025— 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

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

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Student reviews

Original comments behind the course and instructor summaries.

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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
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "364f1ef6e9e3a13a0108e4e8eca9692514fbc10f99e26a1776ed737dd6187ef4",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}