Fall 2026

Cloud Analytics and Artificial Intelligence Tools for Business

GENBUS 308 teaches students to apply statistics and data literacy to business problems using cloud-based analytics and AI tools.

offering recorded2 credits
Recorded instructors · Fall 2026 Bipin Karunakaran3.6/5

Summary

1 / 7

Reviewers generally characterize the course as easy, though one notes grades rely on unpredictable quizzes with unmentioned material. Others highlight the workload involves practical coding and machine learning models.

Grade history

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

Prerequisites

Course map

GEN BUS 307, 317,ECON 400, 410, or declared in undergraduate Business Exchange program

GENBUS 308

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: 3.50/5 from 8 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: 3.3/5 raw quality · 2.6/5 difficulty · 7 reviews

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

Bipin Karunakaran is described as unorganized with confusing code and sidetracking lectures, leading to student frustration. Some reviewers found his quizzes unpredictable and heavily weighted, while others noted he is a tech-focused instructor rather than a polished lecturer.

Other students found Karunakaran friendly, patient, and passionate about data topics, appreciating the hands-on, practical nature of the coursework. These reviewers highlighted that the course is easy, with helpful lectures and slides that support learning real-world business skills.

Recent recorded grades — Fall 2025: 3.92 GPA, 95.5% A/AB (n=89 letter grades); Spring 2026: 3.71 GPA, 83.5% A/AB (n=115 letter grades).

Historical instructors & teaching patterns

BIPIN KARUNAKARAN is recorded teaching in 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 Instruction53 / 5411
DIS 301Classroom Instruction53 / 5411
LEC 002Classroom Instruction52 / 547
DIS 302Classroom Instruction52 / 547

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

Bipin Karunakaran teaches a practical, hands-on course that students found useful for career preparation and easy to succeed in. He is described as friendly, patient, and passionate about data topics.

Recent recorded grades — Spring 2025: 3.69 GPA, 84.6% A/AB (n=26 letter grades); Fall 2025: 3.92 GPA, 95.5% A/AB (n=89 letter grades); Spring 2026: 3.71 GPA, 83.5% A/AB (n=115 letter grades).

difficulty & workload

Reviewers generally characterize the course as easy, though one notes grades rely on unpredictable quizzes with unmentioned material. Others highlight the workload involves practical coding and machine learning models.

Some students report frustration with Karunakaran’s organization, citing invalid code examples, sidetracking, and unclear lectures. One reviewer found the material confusing due to technical errors and poor lecturing.

Topics

  • Business analytics and artificial intelligence.
  • Data literacy.

Skills

  • Applying statistics and data literacy to business problems.
  • Using analytics and AI tools in the cloud.

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
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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
GENBUS 308 · Fall 2026

Cloud Analytics and Artificial Intelligence Tools for Business

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": "1272:231:026555",
    "course_id": "GENBUS 308",
    "course_uid": "course_02d7a8ec033448f8518d0cd4",
    "term_id": "1272",
    "source_course_id": "026555",
    "source_subject_id": "231",
    "title": "Cloud Analytics and Artificial Intelligence Tools for Business",
    "credits_min": 2,
    "credits_max": 2,
    "typically_offered": "Not Applicable"
  }
]
Rate My Professors

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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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.

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Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "90ebfb8452f42f2f25d41f4557fe6ee894d46d1ed7bf00b7e74a540a926dbdc7",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}