Course
MCE A
Term
Spring 2026
Schedule
Mon / Wed Lecture + Fri Recitation
Lessons
6
Course overview
An introduction to mathematical thinking and the role computation plays in reasoning. We work through logic, set theory, and functions carefully and completely, including the structures, before finishing off with elementary number theory. Python runs alongside the mathematics not as the main event but as a tool for testing ideas, checking claims, and building the habit of moving between symbols and executable code.
- Treat code, proofs, and examples as three views of the same idea instead of separate subjects.
- Build from the ground up: concrete objects like numbers, sets, and functions, then logic, then proof by induction, then cardinality and the different sizes of infinity.
- Understand what computation can and can't do, and become confident writing small programs that actually accomplish something useful — even if you never plan to major in CS.
Weekly rhythm
- Read the lesson page first and work through the examples in order.
- Open the linked alternate video only if you want a second explanation or a different pace.
- Do the exercises, then recitation or lab immediately after the notes so the ideas turn into practice.
- Attempt the homework last, without jumping straight to solutions.
Course themes
- Variables, functions, conditionals, loops, and small Python programs.
- Precise mathematical language: sets, logic, vectors, and clean symbolic reasoning.
- Learn to construct complete, rigorous explanations of why things are true, and how to detect and disprove false statements.
- Testing mathematical claims with short programs instead of only reading them.
Prerequisites & corequisites
Prerequisites: MA0 A (Differentiation) and MA0 B (Integration).
- Corequisite: MA1 A (Applied Linear Algebra)
- Corequisite: MA1 B (Calculus I)
- Corequisite: PH1 A (Mechanics)
Course direction
The course is teaching you to think precisely — using set theory as the mathematical backbone and Python as a lightweight sanity check.
References
Outside notes, textbooks, or course pages worth keeping around.
course inspiration
MIT 6.0001: Introduction to Computer Science and Programming in Python
Solid reference for the programming half: lectures, notes, and problem sets.
Main Reference
Brendan W. Sullivan's Everything You Always Wanted To Know About Mathematics
A Guided Journey Into the World of Abstract Mathematics and the Writing of Proofs
python docs
Official Python Tutorial
Use this whenever you want the canonical explanation of syntax and standard features.