Fall 2026

Text Analytics and Business Application

An introduction to text mining and NLP for business applications, covering text representation, topic modeling, and applications like chatbots and recommender systems.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Spring 2024: 3.93 GPA, 96.6% A/AB (n=29 letter grades); Spring 2025: 3.62 GPA, 76.5% A/AB (n=17 letter grades); Spring 2026: 3.81 GPA, 88.9% A/AB (n=18 letter grades).

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 or declared in graduate Business Exchange program
INFOSYS 723

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Prerequisite text tree
  • Graduate/professional standing or declared in graduate Business Exchange program

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

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Calendar & sections

Fall 2026

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Student experience

the class

Recent recorded grades — Spring 2024: 3.93 GPA, 96.6% A/AB (n=29 letter grades); Spring 2025: 3.62 GPA, 76.5% A/AB (n=17 letter grades); Spring 2026: 3.81 GPA, 88.9% A/AB (n=18 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Text mining and natural language processing
  • Representation approaches
  • Topic modeling
  • Chatbots and recommender systems

Skills

  • Making text data usable for analytics
  • Applying text data to descriptive and predictive analytics
  • Text representation approaches
  • Topic modeling

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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Grades over time

Through Spring 2026

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Sources & history

UW–Madison

Catalog & offerings

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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
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "92f649e9b170c71702ec5b5e2784cd42a4fc20ffad34eead46c3d1d2201a243b",
  "requirements_status": "needs_review",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}