Spring 2027

Computing in Data Science and Statistics

Computing in Data Science and Statistics surveys popular tools and frameworks for data scientists, covering Python, machine learning, data visualization, web scraping, and MapReduce.

offering recorded3 credits
Recorded instructors · Spring 2027 Keith Levin2.4/5

Summary

1 / 3

Recent recorded grades — Spring 2024: 3.38 GPA, 78.9% A/AB (n=38 letter grades); Spring 2025: 3.35 GPA, 70.6% A/AB (n=17 letter grades); Spring 2026: 3.40 GPA, 75.0% A/AB (n=24 letter grades).

What you’ll be able to do

  • Understand and apply the basics of the Python programming language and basic programming patterns in both the object-oriented and functional programming frameworks

  • Collect and clean data from a variety of data sources including markup languages from the web, databases, and by using APIs

  • Understand the MapReduce framework and apply it to large-scale data sets in a distributed environment using modern cloud computing platforms

  • Use numerical and scientific computing libraries to build and fit statistical models on large datasets

Source: UW Guide

Grade history

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

Prerequisites

Course map

Declared in Statistics MS or Statistics VISP (undergraduate)

    • Declared in Statistics MS
    • Statistics VISP (undergraduate)
    take one
STAT 606

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Any of
    • Declared in Statistics MS
    • Statistics VISP (undergraduate)

Professors

Spring 2027

Keith Levin

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 1.90/5 from 52 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.

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

Recent recorded grades — Spring 2024: 3.38 GPA, 78.9% A/AB (n=38 letter grades); Spring 2025: 3.35 GPA, 70.6% A/AB (n=17 letter grades); Spring 2026: 3.40 GPA, 75.0% A/AB (n=24 letter grades).

Historical instructors & teaching patterns

KEITH LEVIN is recorded teaching in Spring 2023, Spring 2024, Spring 2025, Spring 2026. 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 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 300

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

Recent recorded grades — Spring 2024: 3.38 GPA, 78.9% A/AB (n=38 letter grades); Spring 2025: 3.35 GPA, 70.6% A/AB (n=17 letter grades); Spring 2026: 3.40 GPA, 75.0% A/AB (n=24 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Python programming, object-oriented and functional programming
  • Scientific computing, machine learning, data visualization
  • Web data collection via scraping and APIs
  • Distributed computing and MapReduce framework

Skills

  • Python programming, object-oriented and functional programming patterns
  • Data collection and cleaning from web, databases, and APIs
  • Building and fitting statistical models using numerical and scientific computing libraries
  • Applying MapReduce framework for large-scale distributed data processing

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

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
STAT 606 · Spring 2027

Computing in Data Science and Statistics

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:932:026408",
    "course_id": "STAT 606",
    "course_uid": "course_cdc21e46ef21cd0cb632076c",
    "term_id": "1274",
    "source_course_id": "026408",
    "source_subject_id": "932",
    "title": "Computing in Data Science and Statistics",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
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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 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "a916c389bb9bc3aa098f91212d486591f2589abcacc18c661dfd27ed7db8659f",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}