Mathematics for Computer Science
Discrete math: the logic, proofs and structures all of CS is built on.
Logic & Propositions
Logic is the grammar of precise thought — the formal language that turns vague reasoning into proofs, programs, and verifiable truth.
Proofs & Proof Techniques
Proofs are the language of mathematics — master the core techniques and you gain the power to establish truth with absolute certainty.
Mathematical Induction & Recursion
Induction is the engine that lets finite proofs capture infinite truths — master it, and recursion becomes a superpower.
Sets, Relations & Functions
The bedrock language of all of mathematics and computer science: how to describe collections, relationships, and mappings with precision.
Combinatorics & Counting
Counting is the foundation of algorithm analysis and probability — master these elegant rules and you can measure the size of any universe of possibilities.
Discrete Probability
Master the mathematics of uncertainty — sample spaces through Bayes' theorem, random variables, expectation, and the union bound — the probabilistic toolkit every CS algorithm relies on.
Graph Theory
Graph theory is the mathematics of relationships — it gives you a universal language for modeling networks, circuits, maps, and algorithms, and the tools to reason about them rigorously.
Number Theory for CS
Number theory is the hidden engine of modern cryptography, hashing, and distributed systems — mastering it transforms you from a user of RSA into someone who truly understands why it works.