Foundations of Algorithms

Module Contents

  1. Introduction to DSA & Algorithms

Zero to Hero starts here. What is an algorithm? Why does Big O matter? Master the fundamentals of computational thinking.

  1. 02. The Hardware Model of Computation

Why algorithms aren’t just math. Learn about CPU caches, RAM latency, and why memory layout determines speed more than Big O sometimes.

  1. 03. The Mathematical Foundations: Proofs

Master the logic behind algorithms. Learn how to prove correctness using Induction, Invariants, and Contradiction.

  1. Time and Space Complexity

Master time and space complexity analysis. Learn how to measure algorithm efficiency using Big O notation with interactive visualizations.

  1. Asymptotic Analysis

Understand Best, Average, and Worst case scenarios. Learn about Big O, Big Omega, and Big Theta notations.

  1. Recursion and Recurrence

Learn how recursion works, visualize the call stack, and analyze recursive algorithms using recurrence relations.

  1. Iterative vs Recursive

Compare iterative and recursive approaches. Learn about tail recursion, stack overflow risks, and when to use which.

  1. Review & Intuition Builder: Foundations

Deep review of DSA foundations with first-principles intuition, proof sketches, interactive complexity estimator, and Java + Go templates.

Foundations of Algorithms

[!NOTE] This module explores the core principles of Foundations of Algorithms, deriving solutions from first principles and hardware constraints to build world-class, production-ready expertise.

1. Practice

[!NOTE] Looking for hands-on algorithmic exercises? We have migrated all coding challenges for this module into the Problem Vault to give you a centralized, focused practice environment.

Module Chapters