Technology Entrepreneurship
An undergraduate course on starting and managing technology-based new ventures, focusing on solving economic and social problems through technology.
Summary
Past student reviews · Phillip Kim
The course required significant pre-class preparation, and participation was weighted heavily in the final grade.
What you’ll be able to do
Describe entrepreneurship and the nature of opportunities including the aspects of technology entrepreneurship that are distinct from other types of entrepreneurship.
Identify the appropriate legal form and potential intellectual property protections for a technology venture.
Design, evaluate, and select appropriate business models and business strategies for technology ventures.
Describe and plan appropriate product development and sales and marketing activities for a technology venture.
Explain basic concepts associated with financial reports in the context of technology venturing.
Identify, evaluate, and propose specific financing options for technology ventures.
Source: UW Guide
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapSophomore standing. Not open to graduate/professional students
“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- All of
- Sophomore standing
- Not eligible with
- graduate/professional students
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
PHILLIP KIM is recorded teaching in Spring 2013, Spring 2014. 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 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
Student experience
the class
Past student reviews · Phillip Kim
Professor Phillip Kim taught this course as a fair grader who helped students learn a lot, though some found his enthusiasm in class to be performative.
Recent recorded grades — Fall 2023: 3.62 GPA, 83.3% A/AB (n=24 letter grades); Fall 2024: 3.31 GPA, 50.0% A/AB (n=18 letter grades); Fall 2025: 3.55 GPA, 75.0% A/AB (n=20 letter grades).
difficulty & workload
Past student reviews · Phillip Kim
The course required significant pre-class preparation, and participation was weighted heavily in the final grade.
Past student reviews · Phillip Kim
Students sometimes had to listen to classmates make pointless comments during class, which was described as a frustrating aspect of the participation-heavy format.
Topics
- Technology entrepreneurship fundamentals
- Legal structures and intellectual property
- Business models and strategies
- Product development and marketing
- Financial reporting concepts
- Venture financing
Skills
- Describing entrepreneurship and technology opportunities
- Identifying legal forms and IP protections
- Designing and evaluating business models
- Planning product development and marketing
- Explaining financial report concepts
- Proposing financing options
Grades
Latest available · Fall 2025— not enough history to project Spring 2027.
Grade distribution · % of letter grades
Grades over time
Through Fall 2025
More grade details Grade mix, volume & source data
Not enough comparable courses for Spring 2027 in UW–Madison.
Sources & history
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.
Selected offering source records
No offering records for the selected term.
Raw records
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Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded 2026-10-14
Model outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
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