Spring 2027

Quantitative Methods for Interdisciplinary Engineering

Review of quantitative topics for engineering applications, including vector calculus, differential equations, linear algebra, complex analysis, transforms, optimization, and numerical methods.

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

Summary

1 / 2

Lectures are small, with a median of 13 enrolled students in the recorded sections.

Section enrollment · Fall 2026 snapshot ↗

What you’ll be able to do

  • Demonstrate various methods for solving 1st and 2nd order ordinary differential equations (ODEs) and apply them to problems such as heat transfer.

  • Employ basic matrix operations for purposes like solving systems of equations, finding determinants, and eigenvalues/eigenvectors for applications such as circuit analysis.

  • Choose numerical methodologies best suited for problems such as solving complex integrals or partial differential equations for applications such as fluid flow within extrusion or injection molding.

  • Communicate mathematical concepts to a general audience.

Source: UW Guide

Grade history

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average GPA
letter grades

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Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
EPD 652

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Prerequisite text tree
  • Graduate/professional standing

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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SectionModeEnrolled / capacityWaitlist

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Meeting source records
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Student experience

the class

Review of topics for engineering applications, including vector calculus, differential equations, linear algebra, complex analysis, Laplace and Fourier transforms, optimization, and numerical methods.

difficulty & workload

No workload feedback recorded.

Topics

  • Vector calculus, differential equations, linear algebra, complex analysis, Laplace and Fourier transforms, optimization, and numerical methods.

Skills

  • Solving first and second order ordinary differential equations for engineering problems like heat transfer.
  • Using matrix operations, determinants, and eigenvalues/eigenvectors for applications like circuit analysis.
  • Selecting numerical methodologies for complex integrals and partial differential equations in fluid flow contexts.
  • Communicating mathematical concepts to a general audience.

Grades

Instructor

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More grade details Grade mix, volume & source data

Sources & history

UW–Madison

Catalog & offerings

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Catalog observation history

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Madgrades

Grade history

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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": "53e62ca0ac0aaa51e557ff9a5ed1c33f18c4de3043578ac15cdbbf442fbb9413",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}