Fundamentals of Set Theory
Fundamentals of Set Theory covers paradoxes, relations, transfinite induction, cardinal/ordinal numbers, real number construction, and the axiom of choice.
Summary
Past student reviews · Uri Andrews
The coursework primarily followed the textbook, providing a standard academic structure for the material.
What you’ll be able to do
Recall and state the formal definitions of the mathematical objects and their properties used in set theory (e.g., sets, power sets, cardinality, ordinals, Zermelo-Fraenkel Axiom System etc.).
Use such definitions to argue that sets do or do not have the condition of a particular property (e.g., that a set is countable, enumerable, well ordered, etc.).
Describe the role of the axiom system of Zermelo-Fraenkel set theory.
Recall and state the standard theorems of set theory (e.g., the Axiom of Choice, Zorn’s Lemma, the Well-ordering Theorem, construction of the real numbers from the natural numbers, etc.) and recall the arguments for these theorems and the underlying logic of their proofs.
Prove or disprove statements related to the above definitions, properties, and theorems using techniques of mathematical argument (direct methods, indirect methods, constructing examples and counterexamples, induction, etc.).
Convey arguments using English and appropriate mathematical terminology, notation and grammar.
Identify applications of course content in areas of modern research.
Source: UW Guide
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course map(MATH 234 and 467) or (MATH 341, 375, 421 or 521) or graduate/professional standing or member of the Pre-Masters Mathematics (Visiting International) Program
This is a best-effort interpretation; check the catalog requirements above.
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
URI ANDREWS is recorded teaching in Fall 2016. 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 |
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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 · Uri Andrews
Students found the course a solid undergraduate introduction to set theory and logic, enhanced by the instructor's engaging lectures and humor.
Recent recorded grades — Fall 2020: 3.42 GPA, 75.0% A/AB (n=12 letter grades); Fall 2022: 2.89 GPA, 44.4% A/AB (n=18 letter grades); Fall 2025: 3.65 GPA, 80.0% A/AB (n=10 letter grades).
difficulty & workload
Past student reviews · Uri Andrews
The coursework primarily followed the textbook, providing a standard academic structure for the material.
Past student reviews · Uri Andrews
Lectures were described as worthwhile due to the instructor's insightful commentary and entertaining delivery style.
Topics
- Set-theoretical paradoxes
- Transfinite induction and recursion
- Cardinal and ordinal numbers
- Axiom of choice
Skills
- Argue about set properties like countability and well-ordering
- Recall standard theorems and proof logic in set theory
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
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Selected offering source records
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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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