Fall 2026

Introduction to Geocomputing

Introduction to Geocomputing focusing on Python scripting for geoprocessing using ArcGIS and open-source libraries.

offering recorded4 credits
Recorded instructors · Fall 2026 Song Gao4.3/5CHEN Wei

Summary

1 / 7

The course is challenging for beginners without coding experience, featuring heavy labs and difficult assignments that require significant effort and practice.

Grade history

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

Prerequisites

Course map

CIV ENGR/​ENVIR ST/​GEOG 377 or concurrent enrollment, or graduate/professional standing

GEOG 378 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Fall 2026

Song Gao

/5Adjusted rating
/5RMP difficulty
captured reviews
About this rating

Raw average: 4.71/5 from 28 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

For this course: 4.4/5 raw quality · 3.5/5 difficulty · 13 reviews

RMP profile ↗ · All captured review dates; profile matched by name.

Song Gao teaches Python programming with geospatial applications, using practical examples and concise lectures that many students find helpful and engaging. Reviewers appreciate his industry knowledge and the relevance of course material to GIS topics.

Some students criticize the course for using outdated methods and lacking depth in geospatial coding instruction. One reviewer found the lectures ineffective and the labs excessively difficult without prior computer science experience.

Recent recorded grades — Fall 2021: 3.66 GPA, 84.4% A/AB (n=32 letter grades); Fall 2022: 3.72 GPA, 86.2% A/AB (n=29 letter grades); Fall 2025: 3.71 GPA, 81.0% A/AB (n=42 letter grades).

No course-specific feedback yet.

Historical instructors & teaching patterns

SONG GAO is recorded teaching in Fall 2017, Fall 2018, Fall 2019, Fall 2020, Fall 2021, Fall 2022, 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

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction46 / 400
LAB 301Classroom Instruction18 / 200
LAB 302Classroom Instruction28 / 200

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
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Student experience

the class

Song Gao teaches Python programming for geospatial computation, with many students finding his lectures helpful, concise, and relevant to GIS applications.

Recent recorded grades — Fall 2024: 3.56 GPA, 80.7% A/AB (n=57 letter grades); Spring 2025: 3.23 GPA, 76.9% A/AB (n=13 letter grades); Fall 2025: 3.71 GPA, 81.0% A/AB (n=42 letter grades).

difficulty & workload

The course is challenging for beginners without coding experience, featuring heavy labs and difficult assignments that require significant effort and practice.

Some students find the content outdated or the teaching ineffective, while others suggest the course structure could better separate programming basics from geocomputing.

Topics

  • Geographic Information Science
  • Geoprocessing
  • Python scripting
  • ArcGIS
  • Open-source libraries

Skills

  • Scripting for Geographic Information Science
  • Geoprocessing with open-source GIS utilities
  • Python scripting with ArcGIS and open-source libraries

Grades

Historical instructor

Fall 2026 · Projected

Before grades are released

– average GPA

Approximate 80% prediction interval

About this estimate

The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.

The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.

8 earlier forecasts · 0.08 GPA average error.

Grades over time

Through Fall 2026

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Fall 2025 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1320 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

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.

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Selected offering source records
GEOG 378 · Fall 2026

Introduction to Geocomputing

Recorded 2026-09-07
Raw records
[
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:416:023341",
    "course_id": "GEOG 378",
    "course_uid": "course_6b09a761a0eeeecdbbd88dc8",
    "term_id": "1272",
    "source_course_id": "023341",
    "source_subject_id": "416",
    "title": "Introduction to Geocomputing",
    "credits_min": 4,
    "credits_max": 4,
    "typically_offered": "Fall, Spring"
  }
]
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Student reviews

Original comments behind the course and instructor summaries.

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Dataset & model

Recorded 2026-09-07

Download the original dataset
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "b77ff9e3e98dc75cc430a526a2b81b6134d3ebeb7257fc2c7112d639a0f07ee6",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}