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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

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Explanations

AI-POWERED

Mock Interview

Explanations

This course includes

15 Playgrounds
12 Quizzes
Course Overview
Course Content
Recommendations

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
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 ...Show More

Course Content

1.

Basics

6 Lessons

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

2.

Formal Analysis Tools

6 Lessons

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

3.

Recursive

8 Lessons

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

4.

Data-Structures

9 Lessons

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

5.

Amortized Analysis

5 Lessons

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

6.

Probabilistic Analysis

5 Lessons

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

7.

Complexity Theory

6 Lessons

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

8.

The End

2 Lessons

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

Course Author

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