Complete Algorithms Complexity and Big O Notation Course

Algorithm and Space Complexity Evaluation

Big O Notation

Interview Coding Tasks Review

Complexity Cases

Complexities Comparison

Mathematical Comparison of Functions

Typical Complexities Evaluation

log N Complexity

Strings and Complexity Evaluation

Recursive Algorithms Complexity

Amortized Analysis

Space Complexity

Basic programming skills (you need to know how to write an "if-else" clause and a "for" loop)

To develop effective code, each developer needs to know how to evaluate the complexity of the algorithms.

The course "Big O Notation. Algorithms Complexity Evaluation." in simple language explains the mathematics behind the complexity of algorithms, cases of complexity, the complexity of recursion, strings, amortized analysis and space complexity. In addition we solve 15 examples, some of which are found in interviews on Google, Facebook, .

We have reworked many books and articles to the most effective for perception and understanding form. As a result this course is independent by its nature and does not require studying of any additional materials. Basic programming skills is the only requirement to understand the course!

Important note: you can always pause the video and process into every aspect of the material in detail!

Bners who want to understand from scratch to professional what complexity evaluation is

Developers of any level who want to pass an interview at companies such as Google, Facebook, Apple

Developers who want to learn how to write effective code

Bner developers curious about complexity evaluation and Big O Notation



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