Master Big O notation & algorithmic time complexity
Explore the fundamentals of Big O notation and algorithmic time complexity with our comprehensive fundamental course. Designed specifically for software engineers preparing for technical interviews, our structured learning path takes you from the basics to advanced concepts.
Course
Reference the Big O notation cheatsheet, to quickly access common time complexities and their practical applications. We've compiled the most frequently encountered algorithms and data structures, complete with their space and time complexity analysis.
Cheat SheetTest your knowledge against practice problems each selected from common technical interview scenarios. Identify Big O notation with real code examples. (Requires an iOS device.)
Practice
Big O Matters
Too many candidates struggle with algorithmic time complexity. Big O notation is a fundamental concept that every software engineer should understand. It's not just about passing technical interviews; it's about writing efficient code that scales.
Don't just take our word for it - see what the developer community is saying about Big O
r/learnprogramming
•A real developer's story of struggling with technical interviews due to Big O notation concepts, highlighting why mastering these fundamentals is crucial for job success.
Read discussionr/webdev
•Even front-end developers face Big O questions in interviews. Understanding time complexity isn't just for backend - it's becoming a universal requirement.
Read discussion