Fall 2026

Introduction to Molecular Spectroscopy

CHEM 763 introduces molecular spectroscopy through quantum mechanics of rotation/vibration, group theory, and resonance spectroscopy in gas and condensed phases.

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Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Spring 2013: 3.77 GPA, 100.0% A/AB (n=13 letter grades); Spring 2015: 4.00 GPA, 100.0% A/AB (n=10 letter grades); Spring 2023: 3.90 GPA, 100.0% A/AB (n=10 letter grades).

Grade history

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average GPA
letter grades
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Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
CHEM 763

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

Prerequisite text tree
  • Graduate/professional standing

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 2013: 3.77 GPA, 100.0% A/AB (n=13 letter grades); Spring 2015: 4.00 GPA, 100.0% A/AB (n=10 letter grades); Spring 2023: 3.90 GPA, 100.0% A/AB (n=10 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Molecular rotation and vibration
  • Group theory
  • Electronic, vibrational, and magnetic resonance spectroscopy
  • Spectroscopy in gas and condensed phases

Skills

  • Apply quantum mechanics to molecular rotation and vibration
  • Apply group theory principles to molecular systems
  • Analyze electronic, vibrational, and magnetic resonance spectroscopy

Grades

Latest available · Spring 2023— not enough history to project Fall 2026.

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 2023

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

Sources & history

UW–Madison

Catalog & offerings

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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": "2a4ccb91444289b988e8f4d48ed570e47093ed0dca18d02925f864e3e0a77504",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}