# Complete Algorithms Complexity and Big O Notation Course

From beginner to professional in 2 hours!

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

What you’ll learn

• Algorithm Time and Space Complexity Evaluation.
• Big O Notation.
• Time Complexity Cases.
• Time Complexities Comparison.
• Mathematical Comparison of Functions.
• Typical Complexities Evaluation.
• log N Complexity.
• Strings and Complexity Evaluation.
• Recursive Algorithms Complexity.
• Amortized Analysis.
• Space Complexity.

Course Content

• Complexity Evaluation –> 16 lectures • 1hr 57min.

Requirements

• 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, Amazon.

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!

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