Python for Applications in Engineering

Covers Python OOP, container types, package management, scientific computing with NumPy/SciPy, and applications to data analysis, ML, and robotics for engineering contexts.

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

Summary

1 / 3

Recent recorded grades — Fall 2022: 3.92 GPA, 100.0% A/AB (n=24 letter grades); Fall 2024: 4.00 GPA, 100.0% A/AB (n=5 letter grades).

What you’ll be able to do

  • Perform computations typically encountered in Engineering (data reading/writing, solving linear systems, perform regressions, etc.) using Python scripts with hundreds to thousands of lines of code

  • Produce a software design solution that can be subsequently implemented in Python to solve a task/practical problem that draws on a computing component

  • Increase their productivity in tasks that require Python programming by taking advantages of 3rd party Python packages

  • Justify the rationale behind using Python in Engineering; explain how this programming language provides support of numerical analysis, statistical analysis, robotics, machine learning, data visualization, computer vision, and AI

Source: UW Guide

Grade history

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average GPA
letter grades
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All recorded terms · compare terms & instructors

Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
EPD 455

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

Prerequisite text tree
  • Graduate/professional standing

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

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Calendar & sections

Spring 2027

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SectionModeEnrolled / capacityWaitlist

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Student experience

the class

Recent recorded grades — Fall 2022: 3.92 GPA, 100.0% A/AB (n=24 letter grades); Fall 2024: 4.00 GPA, 100.0% A/AB (n=5 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Python object-oriented programming: objects, references, classes, and nested objects
  • Python container types: lists, dictionaries, and tuples
  • Python package installation and environment management
  • Scientific computing with NumPy and SciPy
  • Data analysis applications in Python
  • Machine learning applications in Python
  • Embedded systems and robotics applications in Python

Skills

  • Object-oriented programming concepts including classes, objects, and references in Python
  • Installing Python packages and managing development environments
  • Scientific computing using Numpy and SciPy libraries
  • Engineering computations such as data I/O, linear systems, and regression using Python
  • Applying Python to machine learning tasks

Grades

Latest available · Fall 2024— not enough history to project Spring 2027.

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 2024

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "8b9af07ab907ea36433c8dc123eab1cd782e1995859502f8e042102088c15ffc",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}