Fall 2026

Foundational Skills for Business Analysis

GENBUS 106 teaches foundational business analysis skills using Excel, covering data construction, manipulation, and presentation.

offering recorded1 credits
Recorded instructors · Fall 2026 Michael Hernke4.2/5Shubhangi Anup Kumar Katariyar

Summary

1 / 4

The course is online, pass/fail, and considered very easy. Students report spending less than an hour per week, with success relying on watching Excel videos and completing quizzes.

Grade history

average GPA
letter grades

No recorded grade history.

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Prerequisites

Course map

None

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

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  • None

Professors

Fall 2026
/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: 5.0/5 raw quality · 1.6/5 difficulty · 11 reviews

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

Michael Hernke is caring and accommodating, wanting students to succeed. He offers helpful office hours and allows resubmissions even past deadlines. Reviewers praise his supportive attitude and willingness to help those struggling with course material.

The online asynchronous class is straightforward. Hernke provides good feedback and knows his subject matter well. While physical interaction is limited, his digital presence is viewed positively by students engaging with the material.

Historical instructors & teaching patterns

MICHAEL HERNKE is recorded teaching in 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.

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 001Online Only836 / 8417
LEC 100Online Only28 / 500
LEC 002Online Only30 / 302
LEC 003Online Only379 / 3800

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

Meeting source records

No records available.

Student experience

the class

Michael Hernke is consistently described as caring, understanding, and dedicated to student success. Reviewers highlight his willingness to help and his supportive approach to learning.

difficulty & workload

The course is online, pass/fail, and considered very easy. Students report spending less than an hour per week, with success relying on watching Excel videos and completing quizzes.

Students value the flexibility of the asynchronous format and the ability to resubmit assignments. Watching provided Excel videos is recommended over reading materials for mastering basic functions.

Topics

  • Data construction and manipulation
  • Data summarization and analysis
  • Data presentation

Skills

  • Business analysis using Excel
  • Data construction, manipulation, summarization, analysis, and presentation

Grades

Instructor

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Sources & history

UW–Madison

Catalog & offerings

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Catalog observation history

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Selected offering source records
GENBUS 106 · Fall 2026

Foundational Skills for Business Analysis

Recorded 2026-09-07
Raw records
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    "course_id": "GENBUS 106",
    "course_uid": "course_599573b4a6d58f11c011317a",
    "term_id": "1272",
    "source_course_id": "026107",
    "source_subject_id": "231",
    "title": "Foundational Skills for Business Analysis",
    "credits_min": 1,
    "credits_max": 1,
    "typically_offered": "Not Applicable"
  }
]
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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
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