Fall 2026

Data Science Computing Project

STAT 605 teaches tools for collecting, managing, and analyzing large data sets using Linux, R, and distributed computing.

offering recorded3 credits
Recorded instructors · Fall 2026 John Gillett4.2/5Ming Pei

Summary

1 / 3

Recent recorded grades — Spring 2025: 3.72 GPA, 88.9% A/AB (n=9 letter grades); Fall 2025: 3.89 GPA, 95.7% A/AB (n=23 letter grades); Spring 2026: 3.82 GPA, 90.9% A/AB (n=11 letter grades).

Grade history

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

Prerequisites

Course map

Declared in Statistics MS or Statistics VISP

  • Declared in Statistics MS or Statistics VISP
STAT 605

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

Prerequisite text tree
  • Declared in Statistics MS or Statistics VISP

Professors

Fall 2026
/5Adjusted rating
/5RMP difficulty
captured reviews
About this rating

Raw average: 4.39/5 from 67 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 2025: 3.72 GPA, 88.9% A/AB (n=9 letter grades); Fall 2025: 3.89 GPA, 95.7% A/AB (n=23 letter grades); Spring 2026: 3.82 GPA, 90.9% A/AB (n=11 letter grades). Includes jointly taught sections.

Recent recorded grades — Spring 2025: 3.72 GPA, 88.9% A/AB (n=9 letter grades); Fall 2025: 3.89 GPA, 95.7% A/AB (n=23 letter grades); Spring 2026: 3.82 GPA, 90.9% A/AB (n=11 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

JOHN GILLETT is recorded teaching in Fall 2019, Fall 2020, Fall 2021, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Spring 2025, Fall 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

MING PEI is recorded teaching in Fall 2024, Spring 2025, Fall 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

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction15 / 200

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

Meeting source records

Student experience

the class

Recent recorded grades — Spring 2025: 3.72 GPA, 88.9% A/AB (n=9 letter grades); Fall 2025: 3.89 GPA, 95.7% A/AB (n=23 letter grades); Spring 2026: 3.82 GPA, 90.9% A/AB (n=11 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Large data set management and analysis
  • Data science computing tools and environments
  • Data analysis projects

Skills

  • Collecting, managing, and analyzing large data sets
  • Using Linux, R, distributed computing, editors, and git/github
  • Team-based research, development, writing, and presentation

Grades

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

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 Fall 2026 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.

Selected offering source records
STAT 605 · Fall 2026

Data Science Computing Project

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": "1272:932:025309",
    "course_id": "STAT 605",
    "course_uid": "course_6fd1a9b69697ce26f5edccf4",
    "term_id": "1272",
    "source_course_id": "025309",
    "source_subject_id": "932",
    "title": "Data Science Computing Project",
    "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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Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "b3f52ff475f0bfc8b0e0b63758cf765c7552667f396ad9bbd81289a0d5df4ee0",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}