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 advanced analysis topics to provide a more encompassing image of the complexity theory.

Big-O Notation For Coding Interviews and Beyond

<p>In this lesson we won't attempt to describe various tree data-structures and their associated operations. Rather, we'll do a general discussion on how to reason and think about space and time complexity when tree structures are involved.</p>

This lesson is a general discussion on reasoning about space and time complexity of tree structures

Basics

Formal Analysis Tools

Recursive

Data-Structures

Amortized Analysis

Probabilistic Analysis

Complexity Theory

The End

Tree Structures