Programming for Human Behavioral Data Science
Programming for Human Behavioral Data Science covers Python and R fundamentals, data wrangling, and visualization for psychological research.
Summary
Recent recorded grades — Fall 2023: 3.79 GPA, 95.2% A/AB (n=21 letter grades); Fall 2024: 4.00 GPA, 100.0% A/AB (n=23 letter grades); Fall 2025: 4.00 GPA, 100.0% A/AB (n=25 letter grades).
What you’ll be able to do
learn Python and best-practices for writing efficient and understandable code, as informed by psychological research and methods for evaluating human behavior
learn data wrangling in Python and R
learn how to use ggplot to create effective visualizations of complex datasets
learn how to scrape data, manage complex data structures, and perform basicanalyses using machine vision
learn techniques for automating repetitive tasks.
learn how to track and analyze mouse movements
be able to efficiently use and build on existing open-source APIs
Source: UW Guide
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapDeclared in Psychology: Human Behavioral Data Science MS or Psychology PhD
- Declared in Psychology: Human Behavioral Data Science MS or Psychology PhD
“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Declared in Psychology: Human Behavioral Data Science MS or Psychology PhD
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 2023: 3.79 GPA, 95.2% A/AB (n=21 letter grades); Fall 2024: 4.00 GPA, 100.0% A/AB (n=23 letter grades); Fall 2025: 4.00 GPA, 100.0% A/AB (n=25 letter grades).
difficulty & workload
No workload feedback recorded.
Topics
- Programming fundamentals
- Python coding best practices
- Data wrangling in Python and R
- Data visualization with ggplot
- Web scraping and machine vision
- Mouse movement tracking and analysis
- Open-source API usage
Skills
- Writing efficient and understandable Python code
- Data wrangling in Python and R
- Creating effective visualizations with ggplot
- Scraping data and managing complex data structures
- Automating repetitive tasks
- Tracking and analyzing mouse movements
- Using and building on open-source APIs
Grades
Latest available · Fall 2025— not enough history to project Spring 2027.
Grade distribution · % of letter grades
Grades over time
Through Fall 2025
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": "ae5ee539ddd68286d46a21b4b608567767c0805f042e9436a99e87af56b14359",
"requirements_status": "needs_review",
"dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
"observed_at": "2026-10-14 17:50:09.728220+00:00"
}