Big-O Notation & Time Complexity in JavaScript

with Kevin @ KA Education


Welcome to my FREE crash course on Big-O & Time Complexity! As one of the core principles of software development, Big-O frequently appears throughout computer science classes, software engineering technical interviews, and on the job.

A strong grasp of Big-O is like a superpower: it enables you to understand the tradeoffs between various algorithms and/or data structures in terms of overall efficiency and scalability. Simply put, it is an incredibly powerful tool that helps you write better and more efficient code. And if your goal is to step into a career in software engineering or to land your dream job, then I cannot stress how important it is to know Big-O like the back of your hand.

In the lessons below, we'll do a deep dive into Big-O notation and time complexity. I recommend going through each of the lessons in order, because each of the lessons build upon one another. By the time you complete this course, you'll have a in-depth understanding of Big-O & Time Complexity as well as how to correctly apply it to write superior code.

Lastly, if you find this course helpful, then please visit my main website,, where you will find my full-length, comprehensive courses which are all about helping you start or advance your career as a software engineer!

I hope you enjoy the course, see you inside! 😀


Lesson 1 — Introduction to Big O & Time Complexity

Lesson 2 — How do we measure code performance?

Lesson 3 — Counting Operations

Lesson 4 — A Formal Introduction to Big O & Time Complexity

Lesson 5 — Simplifying

Lesson 6 — Logarithmic Time Complexity

Lesson 7 — Conclusion

⭐️ Thanks for stopping by! 😀

If you enjoyed this video series, then be sure to visit where you can find my all of my full-length courses!

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