Quantitative Methods for Geoscience
Quantitative Methods for Geoscience focuses on using MATLAB for programming and data analysis to solve geoscience problems, covering visualization, modeling, and application development.
Summary
Past student reviews · Kurt Feigl
Students rated the difficulty as moderate, noting that the class was accessible to those with no prior coding background.
What you’ll be able to do
Utilize an integrated development environment and documentation to solve geoscientific problems.
Interpret code in a high-level programming language to explain what an existing program does.
Organize geologic data and store them using appropriate data structures.
Develop basic algorithms by using key programming structures including: for-next loops, if-then-else statements, built-in functions, and other custom-built functions.
Plan, design and create a useful, well-documented computer program/utility that has general applicability.
Develop codes that apply appropriate spatio-temporal data analysis routines to geologic datasets.
Integrate data from several data sources to produce publication-ready maps or other geologically relevant figures.
Implement quantitative models for geologic processes using appropriate analytical or numerical toolboxes.
Source: UW Guide 1· UW Guide 2
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapMATH 222, graduate/professional standing, or member of Engineering Guest Students
- MATH 222
- graduate/professional standing
- member of Engineering Guest Students
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Any of
- MATH 222
- graduate/professional standing
- member of Engineering Guest Students
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
KURT FEIGL is recorded teaching in Fall 2018, Fall 2020, Fall 2021, Fall 2023, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.
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
Past student reviews · Kurt Feigl
This course focused on quantitative methods using MATLAB, helping students build a solid grasp of coding basics even without prior experience.
Recent recorded grades — Fall 2018: 3.61 GPA, 66.7% A/AB (n=9 letter grades); Fall 2025: 4.00 GPA, 100.0% A/AB (n=6 letter grades).
difficulty & workload
Past student reviews · Kurt Feigl
Students rated the difficulty as moderate, noting that the class was accessible to those with no prior coding background.
Past student reviews · Kurt Feigl
Dr. Feigl was described as helpful in answering questions and supporting student understanding, making the course a useful part of the degree.
Topics
- Data visualization, figure development, data processing automation, statistical and time-series analysis, image processing, mapping, and optimization
- Integration of multiple data sources for publication-ready maps and figures
- Quantitative modeling of geologic processes using analytical or numerical toolboxes
Skills
- Practical programming and data analysis using MATLAB
- Data visualization, automation, statistical/time-series analysis, image processing, mapping, and optimization
- Algorithm development using loops, conditionals, and functions
- Quantitative modeling of geologic processes
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
[]
Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
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": "b44882c7e3667c29993d24d186c4e60f2b096b324fb387207a847a9dda4133e0",
"requirements_status": "valid",
"dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
"observed_at": "2026-10-14 17:50:09.728220+00:00"
}