Graph theory

Deterministic finite automaton (DFA)

Set (mathematics)

Set theory

Proof by contradiction

Contraposition

Quantification (logic)

Logical connective

Predicate (mathematical logic)

Function (mathematics)

Constant (mathematics)

Quantifier (logic)

Binary relation

Reflexive relation

Symmetric relation

Transitive relation

Equivalence relation

Equivalence class

Domain of a function

Codomain

Injective function

Surjective function

Bijection

Function composition

Cardinality of the continuum

Cantor's diagonal argument

Mathematical induction

Strong induction

Formal language

Direct proof

Propositional calculus (Propositional logic)

CS 103A Math Problem-Solving Strategies Stanford University Winter 2020 CS 103A serves as an additional review course for CS103 students, focusing on strengthening proof-based mathematics skills and general problem-solving strategies in a context closely tied to CS103. Math, like programming, is a skill that takes practice to develop. In CS103A, we'll
provide extra review of the topics from CS103 and discuss general problem-solving
strategies that often come up in proof-based mathematics. We hope that the course
helps solidify the concepts from CS103 and provides you with a set of tools you can
use to confront challenging math problems with confidence.

If you're interested in taking CS103 but feel like you could use a little bit more practice
and review, this is the course for you!  CS103A has CS103 as a corequisite. This class is specifically designed as an add-on
course for CS103 and the material and presentation will be tailored to current CS103
students. As a result, you must be enrolled in CS103 to take CS103A. 

CS 103A Math Problem-Solving Strategies

Mathematical Foundations

The Pigeon Hole Principle

Statement (logic)

Truth table

Conjunctive normal form (CNF)

Disjunctive normal form (DNF)

First-order logic

Relation (mathematics)

Bijection, injection and surjection

Number theory

Modular arithmetic

RSA (cryptosystem)

Binomial theorem

Probability theory

Independence (probability theory)

Random variable

Expectation

Conditional probability

Tree (graph theory)

Random walk on graphs

CSCI 0220 Discrete Structures and Probability Brown University Spring 2023 CSCI 0220 provides a foundation in discrete math and probability theory. Key topics include logic, set theory, number theory, combinatorics, graph theory, and probability. No prior math background assumed. Aims to develop problem solving, communication, and collaboration skills. Introduces new concepts and ways of thinking to enable analyzing problems arising in computer science. Beginner-friendly introduction to core mathematical concepts underlying many aspects of CS. I don't know about you, but we're feeling 22! This class gives you the tools to explore interesting questions and convince yourself and others of their answers. You'll be introduced to new worlds of ideas and ways of thinking. We'll learn about Set Theory, Logic, Number Theory, Combinatorics, Graph Theory, and Probability. If these topics sound unfamiliar, not to fear: you're in exactly the right place! This course assumes no prior experience with these topics.  CS can feel like a very applied field. Why learn math?

- Problem solving
- Communication
- Collaboration

A key result of this class: you’ll have a vocabulary for discussing certain kinds of
problems that appear in many different contexts, and a toolbox of general approaches
for solving them.

A vital point of computer science (academic, industry, hobbyist): *communication*. Our expectations from you

- No mathematical background is assumed. We’re not doing calculus, statistics, ...
- Approach things with an open mind.
- Try to communicate clearly and concisely.
- Respect your classmates and TAs: we’re in this together.
- Let us know how you’re doing! [Mathematics for Computer Science — Lehman, Leighton, Meyer](https://cs22.io/static/files/Mathematics_for_Computer_Science.pdf)

Reading (and purchasing!) this textbook is not required, though many students in the past have found it helpful in reinforcing what's covered in lecture! 

CSCI 0220 Discrete Structures and Probability

Graph theory

2 courses cover this concept

CS 103A Math Problem-Solving Strategies

CSCI 0220 Discrete Structures and Probability