Spring 2027

Randomized Linear Algebra and Applications

A systematic study of randomized linear algebra solvers covering mathematical backgrounds, algorithms like randomized SVD and matrix completion, and their implementation and application.

offering recorded3 credits
Recorded instructors · Spring 2027 Qin Li3.7/5

Summary

1 / 3

Recent recorded grades — Fall 2024: 3.83 GPA, 100.0% A/AB (n=23 letter grades); Spring 2026: 3.69 GPA, 88.5% A/AB (n=26 letter grades).

What you’ll be able to do

  • Implement, in a computer language, the principal linear algebra solvers, namely, matrix completion, randomized SVD, matrix sketching, and the Kaczmarz algorithm.

  • Identify the conditions, assumptions, and effectiveness of the principal linear algebra solvers.

  • Reproduce the proof strategies for effectiveness of these algorithms and summarize the main parts of these proofs.

  • Apply random linear algebra solvers to problems from image reconstruction, inverse problems and topic modeling.

  • Model problems from the physical or social sciences in matrix form and identify regimes to apply linear algebra solvers.

Source: UW Guide

Grade history

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

Prerequisites

Course map

Graduate/professional standing or declared in Mathematics VISP (graduate or dissertator)

    • Graduate/professional standing
    • declared in Mathematics VISP (graduate or dissertator)
    take one
MATH 718

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

Prerequisite text tree
  • Any of
    • Graduate/professional standing
    • declared in Mathematics VISP (graduate or dissertator)

Professors

Spring 2027

Qin Li

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 3.79/5 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.

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

Recent recorded grades — Spring 2026: 3.69 GPA, 88.5% A/AB (n=26 letter grades).

Historical instructors & teaching patterns

QIN LI is recorded teaching in 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 / 400

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 — Fall 2024: 3.83 GPA, 100.0% A/AB (n=23 letter grades); Spring 2026: 3.69 GPA, 88.5% A/AB (n=26 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Randomized Kaczmarz, stochastic gradient descent, randomized SVD, random sketching, matrix completion, and compressive sensing
  • Inverse problems, machine learning, and scientific computing applications
  • Image reconstruction and topic modeling

Skills

  • Implementing randomized linear algebra solvers in a computer language
  • Reproducing proof strategies for algorithm effectiveness
  • Applying random linear algebra solvers to image reconstruction, inverse problems, and topic modeling
  • Modeling scientific problems in matrix form and identifying applicable solver regimes

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
MATH 718 · Spring 2027

Randomized Linear Algebra and Applications

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": "1274:600:026586",
    "course_id": "MATH 718",
    "course_uid": "course_4c518c7aee577750986dc7c8",
    "term_id": "1274",
    "source_course_id": "026586",
    "source_subject_id": "600",
    "title": "Randomized Linear Algebra and Applications",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
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Madgrades

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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": "4f9379f9af12ea6464ca479adc0b7019f708bd8d4bf5bfa8eb59e6056eaa9fd7",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}