Fall 2026

Introduction to Fourier Analysis

Introduction to Fourier Analysis covers Fourier series, integrals, and their applications.

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

Summary

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Recent recorded grades — Spring 2016: 3.23 GPA, 45.5% A/AB (n=11 letter grades); Fall 2021: 3.90 GPA, 90.0% A/AB (n=10 letter grades); Fall 2023: 3.31 GPA, 75.0% A/AB (n=8 letter grades).

Grade history

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average GPA
letter grades
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Prerequisites

Course map

MATH 521 or graduate/professional standing or member of the Pre-Masters Mathematics (Visiting International) Program

    • MATH 521
    • graduate/professional standing
    • member of the Pre-Masters Mathematics (Visiting International) Program
    take one
MATH 627

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

Prerequisite text tree
  • Any of
    • MATH 521
    • graduate/professional standing
    • member of the Pre-Masters Mathematics (Visiting International) 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 2016: 3.23 GPA, 45.5% A/AB (n=11 letter grades); Fall 2021: 3.90 GPA, 90.0% A/AB (n=10 letter grades); Fall 2023: 3.31 GPA, 75.0% A/AB (n=8 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Fourier series
  • Fourier integrals
  • Applications of Fourier analysis

Skills

  • Fourier series and integrals
  • Applications of Fourier analysis

Grades

Latest available · Fall 2023— 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
C
D
F

Grades over time

Through Fall 2023

More grade details Grade mix, volume & source data

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Sources & history

UW–Madison

Catalog & offerings

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Dataset & model

Recorded 2026-09-07

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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": "a7701828313147bb7c3e77a3a894266d6497f58029d1be456db3ad4cd27adaa5",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}