Big-O Notation For Coding Interviews and Beyond

The ultimate guide to Big-O notation for coding interviews, developed by FAANG engineers. Learn algorithm complexity in simple terms and get interview-ready in just a few hours.

Beginner

47 Lessons

10h

Certificate of Completion

The ultimate guide to Big-O notation for coding interviews, developed by FAANG engineers. Learn algorithm complexity in simple terms and get interview-ready in just a few hours.

AI-POWERED

Mock Interview

Explanations

AI-POWERED

Mock Interview

Explanations

This course includes

15 Playgrounds

12 Quizzes

This course includes

15 Playgrounds

12 Quizzes

Course Overview

This course is intended for professionals that lack formal education in computer science, and that are in search of a simple and practical guide to algorithmic complexity. The course explains the concepts in layman's terms, and teaches how to reason about the complexity of algorithms without requiring one to have an extensive mathematical skillset. This course can also be handy for revising complexity concepts or Big-O analysis before interviews. Finally, the content also scratches the surface of some advan...Show More

Course Content

Basics

Get familiar with the importance of time and space complexity, algorithm performance analysis, and instruction counting.

Introduction Need for Speed Analyzing Algorithms

Analyzing Algorithms Part II Analyzing Algorithms Part III

Problem Set 1

Formal Analysis Tools

Get started with formal tools for analyzing algorithm performance, growth, and complexity.

Functions and Their Growth Theta Notation Big O and Big Omega Notations Small omega and Small o Notations Problem Set 2 Solution Set 2

Recursive

Examine recursion, binary search, permutations, dynamic programming, and algorithm efficiency analysis.

Recurrence Recurrence Part II Binary Search - Recursive Implementation

Permutations Dynamic Programming Top Down and Bottom Up Approaches Problem Set 3 Solution Set 3

Data-Structures

Grasp the fundamentals of essential data structures and their complexities for efficient coding.

Array Linked List Hash Table Doubly Linked List Stacks and Queues Tree Structures Problem Set 4 Solution Set 4 Priority Expiry Cache Problem

Amortized Analysis

Take a closer look at the cost efficiency of operations using amortized analysis methods.

Cost Over Sequence of Operations Dynamic Array Fancy Stack Problem Set 5 Solution Set 5

Probabilistic Analysis

5 Lessons

Understand probability, random variables, probability distributions, expected value, and the Tinder Problem.

Complexity Theory

6 Lessons

Build on the importance of understanding complexity theory, P vs NP, and problem classes.

The End

2 Lessons

Grasp key Big-O complexities for algorithms and data structures to make informed decisions.

Course Author

Part of the Java Interview Prep Path

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Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

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