Fall 2026

Interactive Data Analytics

ISYE 649 teaches cognitive engineering approaches to data visualization and interactive analytics using R.

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

Summary

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Recent recorded grades — Fall 2023: 3.66 GPA, 88.7% A/AB (n=53 letter grades); Fall 2024: 3.83 GPA, 96.4% A/AB (n=55 letter grades); Fall 2025: 3.79 GPA, 96.6% A/AB (n=29 letter grades).

Grade history

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average GPA
letter grades
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Prerequisites

Course map

I SY E/​PSYCH 349 and (I SY E 210,E C E 331,MATH/​STAT 310,STAT 312, 324, or 340), graduate/professional standing, or member of Engineering Guest Students

ISYE 649

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

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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Meeting source records

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Student experience

the class

Recent recorded grades — Fall 2023: 3.66 GPA, 88.7% A/AB (n=53 letter grades); Fall 2024: 3.83 GPA, 96.4% A/AB (n=55 letter grades); Fall 2025: 3.79 GPA, 96.6% A/AB (n=29 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Human-computer interaction.
  • Visualization design principles and human capabilities.
  • Visual analytics.

Skills

  • Creating static and interactive visualizations using R.
  • Applying cognitive engineering principles to visualization design.

Grades

Latest available · Fall 2025— 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
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BC
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Grades over time

Through Fall 2025

More grade details Grade mix, volume & source data

Not enough comparable courses for Fall 2026 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

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Catalog observation history

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Grade history

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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": "ae0d8f6f8e6cf5fb9f36cf48d9f77a319535b51245d747e53262cf68df86049d",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}