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.
Summary
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
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapGraduate/professional standing
- Graduate/professional standing
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Graduate/professional standing
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Spring 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
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.
Grade distribution · % of letter grades
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
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
Observations at scan time; dates do not imply when a catalog change took effect.
Selected offering source records
No offering records for the selected term.
Raw records
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Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
No records available.
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded 2026-10-14
Model outputs & technical records
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"
}