Spring 2027

Research Computing in Atmospheric and Oceanic Sciences

Hands-on introduction to open-source research computing tools, including Python, Unix, and git, for analyzing and visualizing atmospheric and oceanic science data.

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

Summary

1 / 4

Recent recorded grades — Fall 2023: 3.58 GPA, 76.9% A/AB (n=13 letter grades); Fall 2024: 3.68 GPA, 78.9% A/AB (n=19 letter grades); Fall 2025: 3.60 GPA, 83.3% A/AB (n=24 letter grades).

What you’ll be able to do

  • Become familiar with computing tools that are useful in managing, analyzing, and visualizing atmospheric and oceanic science data, including Unix, git, and Python

  • Understand multiple Python packages that are critical for atmospheric and oceanic science data analysis and use these packages to analyze and visualize atmospheric and oceanic science datasets

  • Develop proficiency in the use of version control and other elements of open science best practices

  • Implement a reproducible data analysis workflow that incorporates Python computing tools and version control and apply it to an unfamiliar dataset or new research topic

Source: UW Guide

Grade history

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average GPA
letter grades
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Prerequisites

Course map

(MATH 234 and COMP SCI 220) or graduate/professional standing

ATMOCN 573 used by

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

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Professors

Spring 2027

No instructors recorded for this selection.

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Calendar & sections

Spring 2027

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Student experience

the class

Recent recorded grades — Fall 2023: 3.58 GPA, 76.9% A/AB (n=13 letter grades); Fall 2024: 3.68 GPA, 78.9% A/AB (n=19 letter grades); Fall 2025: 3.60 GPA, 83.3% A/AB (n=24 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Python basics, data structures, environments, and packages
  • Version control, code sharing, collaboration, and open science best practices
  • Unix, git, and Python for data management, analysis, and visualization

Skills

  • Python programming, data structures, and visualization for atmospheric and oceanic science datasets
  • Version control, code sharing, collaboration, and open science best practices
  • Managing, analyzing, and visualizing data using Unix, git, and Python

Grades

Latest available · Fall 2025— 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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D
F

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

UW–Madison

Catalog & offerings

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Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "87ef5434b3c6e8cfa00c878048c83cef7793616a71a8ae256e4e5d15c88bd5b0",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}