Immerse yourself in the world of search and sorting algorithms. Learn their implementations, complexities, and real-world applications.
Master the fundamental concepts behind algorithms
Understand Big O notation and performance analysis
See examples in multiple programming languages
Big O notation is a mathematical notation that describes the limiting behavior of a function as the argument approaches a particular value or infinity. In computer science, it is used to classify algorithms based on how their runtime or space requirements increase as the input size increases.
Measures the amount of time an algorithm takes to complete based on the input size. It helps us understand how the algorithm's performance scales with larger inputs.
Measures the amount of memory space required by an algorithm based on the input size. This includes both auxiliary space and the space used by the input.