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Big-O Notation For Coding Interviews and Beyond
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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.

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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...Show More

Course Content

47 Lessons12 Quizzes

Basics

6 Lessons

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

6 Lessons

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

8 Lessons

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

9 Lessons

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

Priority Expiry Cache Problem

Amortized Analysis

5 Lessons

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

Cost Over Sequence of Operations

Probabilistic Analysis

5 Lessons

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

Quantifying Chance & Randomness

Random Variables

Probability Distribution

Expected Value of a Random Variable

The Tinder Problem

Complexity Theory

6 Lessons

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

Why should I bother?

P and NP classes

Get Rich with Complexity

NP-Complete and NP-Hard

Between P and NP ?

Problem Set 6

The End

2 Lessons

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

Cheat Sheet

Epilogue

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

C. H. Afzal

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