Complete Space and Time Complexity in Data Structure and Algorithms

### Link to the coursework

https://www.wscubetech.com/resources/dsa/time-complexity

### Learning Objectives

- [ ] Define Big O notation
- [ ] List 8 common levels of time complexity
- [ ] Identify the time complexity of given common (named) algorithms

### Why are we doing this?

This is a primer on space and time complexity. It's basically a reference guide. _You do not need to memorise this information._ Read through it and make notes for yourself. Make sure you can answer the following questions:

- What is Big O Notation?
- Which has a higher complexity, bubble sort or timsort?
- What's the problem with nested loops?

Complete

1. https://www.wscubetech.com/resources/dsa/time-complexity
1. https://www.wscubetech.com/resources/dsa/space-complexity

### Maximum time in hours

3

### How to get help

Share your blockers in your class channel
https://curriculum.codeyourfuture.io/guides/getting-help/asking-questions/

### How to submit

No submission step. This is background reading for your own understanding.

### Anything else?

Enjoy this folk dance bubble sort: https://www.youtube.com/watch?v=Iv3vgjM8Pv4

Comece pelo material vinculado sobre complexidade de tempo e complexidade de espaço. Leia os dois recursos e use as perguntas listadas para verificar seu entendimento da notação Big O, das complexidades comuns, dos algoritmos de ordenação e dos loops aninhados; não há uma etapa de envio, portanto concluir significa terminar a leitura e fazer anotações pessoais.

Escrita pelo modelo de indexação a partir do texto da issue.