📐 The Grammar of CS

Discrete Mathematics

Continuous math deals with smooth curves; Discrete Math deals with distinct steps—just like computers (0s and 1s). It bridges logic and executable code.

🚀 Practical Applications

🔌 Logic

Minimizing boolean expressions for cheaper, faster CPUs.

🕸️ Graph Theory

Algorithms for GPS, social networks, and routing.

🔐 Cryptography

Group Theory secures data transmission.

🗺️ Course Roadmap

Module 1: Logic & Rules of Inference

What: Propositional Logic, Predicates, Quantifiers, Rules of Inference.

Why: Logic is the CPU's language—the basis of every program.

1-4: Connectives, Arguments, Predicates, TranslationComing Soon

Module 2: Sets, Functions, & Relations

What: Set Operations, Functions, Bijections, Equivalence Relations.

Why: Sets are the basis of databases; functions explain input-output mappings.

5-9: Venn Diagrams, Mappings, Bijections, EquivalenceComing Soon

Module 3: Posets, Lattices, & Boolean Algebra

What: Partial Orders, Hasse Diagrams, Lattice Theory, Boolean Algebra.

Why: Analyze hierarchy and order for dependency resolution.

10-13: Hasse Diagrams, LUB/GLB, Distributive LatticesComing Soon

Module 4: Algebraic Structures (Group Theory)

What: Semigroups, Monoids, Groups, Subgroups, Cyclic Groups.

Why: Groups power RSA and Elliptic Curve Cryptography.

14-17: Monoids, Abelian Groups, Lagrange, GeneratorsComing Soon

Module 5: Combinatorics & Practice

What: Pigeonhole Principle, Recurrence Relations, Generating Functions.

Why: Analyze algorithm complexity and prove limits.

18-22: Pigeonhole, Recurrences, Graph Theory PracticeComing Soon
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