Fall 2026

Introduction to Computing

Introduction to Computing provides a broad overview of computing topics like security, robotics, and AI, and algorithmic problem solving.

offering recorded3 credits
Recorded instructors · Fall 2026 Jeff Nyhoff3.5/5

Summary

1 / 6

The workload involves daily in-person attendance and completing assignments posted after lectures, often requiring students to bring fully charged computers. Some reviewers note that outside work can be long and that the Canvas page is disorganized.

Grade history

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

Prerequisites

Course map

MATH 96or placement into MATH 141. MATH 118 does not fulfill the prerequisite. Not open to students with credit forCOMP SCI 300 or 320

COMPSCI/LIS 102

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

Prerequisite text tree

Professors

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

Raw average: 3.35/5 from 37 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: 3.8/5 raw quality · 1.4/5 difficulty · 27 reviews

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

Jeff Nyhoff is frequently described as a chill and responsive professor. Reviewers note there are no quizzes or tests, as grading relies on lecture demos and homework. He also provides grace points to accommodate missed classes.

Some students criticize Nyhoff for arriving late to mandatory 8 a.m. sessions and enforcing a strict attendance policy. Others find his lectures rambling and disorganized, citing excessive busywork and irrelevant tangents. One reviewer reported he was dismissive when asked to post materials early.

Recent recorded grades — Spring 2025: 3.81 GPA, 88.6% A/AB (n=176 letter grades); Fall 2025: 3.93 GPA, 97.4% A/AB (n=195 letter grades); Spring 2026: 3.87 GPA, 94.3% A/AB (n=194 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

JEFF NYHOFF is recorded teaching in Fall 2023, Spring 2024, 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 Instruction114 / 2650
LEC 001Classroom Instruction41 / 2650

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

Jeff Nyhoff teaches a very easy course with no quizzes or tests, relying instead on lecture demos and homework. Reviewers describe the class as an easy pass, though some find the lecture-heavy format and his tendency to ramble annoying.

Recent recorded grades — Spring 2025: 3.81 GPA, 88.6% A/AB (n=176 letter grades); Fall 2025: 3.93 GPA, 97.4% A/AB (n=195 letter grades); Spring 2026: 3.87 GPA, 94.3% A/AB (n=194 letter grades).

difficulty & workload

The workload involves daily in-person attendance and completing assignments posted after lectures, often requiring students to bring fully charged computers. Some reviewers note that outside work can be long and that the Canvas page is disorganized.

Students report frustration with Nyhoff's tardiness, disorganized Canvas page, and tendency to go off-topic during lectures. Conversely, others appreciate his kindness and fast response times when students are struggling with assignments.

Topics

  • Security, robotics, and artificial intelligence
  • Algorithms and problem solving

Skills

  • Understanding algorithms and problem solving
  • Creative application design in introductory coding

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

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AB
B
BC
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D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · 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

1283 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
COMPSCI/LIS 102 · Fall 2026

Introduction to Computing

Recorded 2026-09-07
COMPSCI/LIS 102 · Fall 2026

Introduction to Computing

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": "1272:266:023191",
    "course_id": "COMPSCI/LIS 102",
    "course_uid": "course_72fca04984de023263764214",
    "term_id": "1272",
    "source_course_id": "023191",
    "source_subject_id": "266",
    "title": "Introduction to Computing",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Fall, Spring"
  },
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:544:023191",
    "course_id": "COMPSCI/LIS 102",
    "course_uid": "course_72fca04984de023263764214",
    "term_id": "1272",
    "source_course_id": "023191",
    "source_subject_id": "544",
    "title": "Introduction to Computing",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Fall, Spring"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
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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
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "f7d068d53694860d51e4055d9d781cf687d4d213b2961432f3e089b2c2697409",
  "requirements_status": "needs_review",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}