Fall 2026

Business Analytics II

Business Analytics II focuses on predictive and prescriptive analytics using modeling and optimization tools.

offering recorded3 credits
Recorded instructors · Fall 2026 Michael Hernke4.2/5Sung Kim3.8/5Haotian Zhang +4 more

Summary

1 / 7

The class is tough with fast-paced material. Students must practice Excel skills and complete participation activities independently. Reviewers disagree on the final exam's impact, calling it easy or insufficient for top 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

GEN BUS 106 and 306, or declared in undergraduate Business Exchange program

GENBUS 307 used by

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

Prerequisite text tree

Professors

Fall 2026

Michael Hernke

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

Raw average: 4.44/5 from 41 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: 4.0/5 raw quality · 3.3/5 difficulty · 7 reviews

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

Michael Hernke is described as patient, helpful, and passionate, using stories to engage students and offering accommodations for personal struggles. Reviewers appreciate his unique, engaging lecturing style and his desire to see students succeed.

Some students find his recorded lectures boring and dull, preferring in-person instruction. Others report unfair grading despite hard work, leading to negative experiences and warnings against taking his class.

Recent recorded grades — Spring 2025: 3.37 GPA, 69.0% A/AB (n=287 letter grades); Fall 2025: 3.23 GPA, 62.3% A/AB (n=451 letter grades); Spring 2026: 3.27 GPA, 64.6% A/AB (n=206 letter grades). Includes jointly taught sections.

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

Raw average: 4.00/5 from 12 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 — Fall 2023: 3.17 GPA, 56.4% A/AB (n=381 letter grades); Fall 2024: 3.23 GPA, 59.1% A/AB (n=399 letter grades); Fall 2025: 3.23 GPA, 62.3% A/AB (n=451 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

Paul Hoban taught this course historically, with reviews noting his interactive lectures and clear concept explanations. Students found the class hard due to difficult exams and significant outside prep work, though some found the activities manageable with peer collaboration.

MICHAEL HERNKE is recorded teaching in Fall 2016, Spring 2017, Fall 2017, Spring 2018, Fall 2018, Spring 2019, Fall 2019, Spring 2020, Fall 2020, Fall 2021, Spring 2022, 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.

PAUL HOBAN is recorded teaching in Spring 2017, Spring 2018, Spring 2019, Spring 2020. Recorded history may be incomplete and does not establish a future schedule.

REMI DAVIET is recorded teaching in Spring 2022, Spring 2023, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

SUNG KIM is recorded teaching in Fall 2016, Fall 2017, Fall 2018, Fall 2019, Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024, Fall 2025. 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 Instruction45 / 1100
LEC 002Classroom Instruction62 / 1100
LEC 003Classroom Instruction110 / 1117
LEC 004Classroom Instruction110 / 1100
LEC 005Classroom Instruction111 / 1115
DIS 301Classroom Instruction45 / 1100
DIS 302Classroom Instruction62 / 1100
DIS 303Classroom Instruction110 / 1107
DIS 304Classroom Instruction110 / 1100
DIS 305Classroom Instruction111 / 1115

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

Michael Hernke is described as patient, passionate, and accommodating, with students noting his unique and engaging lecturing style. Conversely, one reviewer found his recorded lectures dull and another reported an unfair grading experience despite hard work.

Recent recorded grades — Spring 2025: 3.31 GPA, 64.2% A/AB (n=425 letter grades); Fall 2025: 3.23 GPA, 62.3% A/AB (n=451 letter grades); Spring 2026: 3.22 GPA, 58.9% A/AB (n=419 letter grades).

difficulty & workload

The class is tough with fast-paced material. Students must practice Excel skills and complete participation activities independently. Reviewers disagree on the final exam's impact, calling it easy or insufficient for top grades.

Hernke is noted for being accommodating regarding exams and assignments, sometimes offering extensions for personal struggles. Conversely, one student reported a horrible grade despite significant effort, describing the experience as totally unfair.

Topics

  • Predictive analytics and causal inference.
  • Prescriptive analytics and decision modeling.
  • Modeling and optimization tools.

Skills

  • Applying modeling and optimization tools for analytic methodologies.
  • Inferring causal relationships and forecasting future outcomes.
  • Formulating decision models to identify optimal actions.

Grades

Historical instructor

Fall 2026 · Projected

Before grades are released

– average GPA

Approximate 80% prediction interval

About this estimate

The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.

The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.

8 earlier forecasts · 0.08 GPA average error.

Grades over time

Through Fall 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
GENBUS 307 · Fall 2026

Business Analytics II

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": "1272:231:024535",
    "course_id": "GENBUS 307",
    "course_uid": "course_412bfa78215919930228ef5e",
    "term_id": "1272",
    "source_course_id": "024535",
    "source_subject_id": "231",
    "title": "Business Analytics II",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
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.

Explore recorded grades
Dataset & model

Recorded 2026-09-07

Download the original dataset
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "4a109ac8776274bbd9739222952d3c42850cbac2e1a17ef36f653b694c80e9fd",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}